Introduction to Operations and Supply Chain Management, 5th Edition Cecil B Bozarth Solution Manual by Ace Test Banks

Instructor’s Solution Manual for Introduction to Operations and Supply Chain Management Geoff Willis

Introduction to Operations and Supply Chain Management Fifth Edition

Cecil C. Bozarth Robert B. Handfield

1. One could argue that Alcoa is not the first entity in the supply chain because other companies supply it with the tools and materials to get the aluminum out of the ground. Other suppliers for Anheuser-Busch would be the company that provides the hops and grains required to make its beer, and the supplier of brewing equipment. Anheuser-Busch needs to share sales information and forecasts with its suppliers so that they can plan capacity and production levels. All of the companies within the supply chain need to be as transparent with their data as possible so that products can be made and shipped out to the customers with a minimum of waste. 2. While it is true that operations management and supply chain management are integral to manufacturing firms, it is false that operations and supply chain apply only to manufacturers. Service industries also source products and services, and in some cases, need to consider how these will be delivered to the final customer. Amazon, which uses UPS to make deliveries, is a prime example. 3. There are many different supply chains that support products like the Apple iPhone, and without these the iPhone would not be nearly as successful. Apple has a company that creates the physical phone itself, suppliers that make the electronic components that go inside the phone, and even partner companies that monitor satellites to give the phone navigation capability. Apple uses the “App Store” to virtually manage the software application on phones, and through this store they can market apps, create the purchase transaction, and simultaneously deliver the good to the consumer. 4. There are numerous examples of where poor supply chain management undercuts a business. For example, a product may be well-designed, but if the company cannot source quality inputs, cannot produce the product to cost or quality targets, and cannot deliver it in a timely manner, the product will fail in the marketplace.

1. The key advantage of releasing a new product during the late-year holiday season is the potential spike in demand, especially for consumer goods like the iPod. The large seasonal “bumps” from the introduction of new generations of products coupled with the holiday shopping season pose significant challenges for its supply chain partners since they need to respond quickly to new requirements. Apple’s business strategy puts a premium on suppliers that can demonstrate volume flexibility (not to mention, high levels of quality conformance) because Apple sells considerably fewer iPods from March to September than October to February, and Apple needs suppliers that can give them varying amounts of product in limited time frames. The match between supply and demand for the iPhone X is not as good as recent model introductions; demand far exceeded supply. 2.

One example is McDonald’s; their mission statement is as follows: McDonald’s brand mission is to “be our customers’ favorite place and way to eat.” McDonalds’ worldwide operations have been aligned around a global strategy called- ‘Plan to Win,’ centering on the five basics of an exceptional customer experience—People, Products, Place, Price, and Promotion. This is a useful mission statement because it addresses different functional areas of the company and in the end focuses on people and the customers’ experience. Their operations and supply chain strategies are consistent with the mission statement because they execute their worldwide operations through an interconnected global strategy -.

3. The business strategy and the operation strategies are so interconnected that they can flow both ways, and core competencies derived within the operations and supply chain areas can be exploited through broader business strategies. Examples will vary. 4. Strategy experts have long said it’s not what a strategy document may say; it’s what the firm does that counts. For example, if the strategy document says that the firm will place a premium on introducing new, innovative products, but the firm’s actual investments are in producing large quantities of standard products at the lowest possible cost, then it is the pattern of decisions it makes that set the strategy. The risk of not having an explicit rendering of the firm’s strategy is .

that actions may be interpreted differently by individuals that have incomplete information about the motivations for the actions. 5. Answers will vary, but common responses include low cost, perceived quality of instruction or value of degree in the chosen field, flexibility of course offerings, availability of online classes, and proximity to home or work. Depending on the student, these items may be classified as order winners or qualifiers. 6. Customers can perceive the value of the same product or service differently because they evaluate products based on multiple performance dimensions and can assign different values for each of these dimensions. This means that the companies that can develop the best mix of the performance dimensions for their customer base will be able to maximize their product value and profits. Companies need to find ways to maximize the value of their performance dimensions so that they can deliver the best, most desirable product to their consumers. 7. Not all firms have to both develop and exploit core competencies in the operations and supply chain areas to be successful in business. For example, a local gas station may succeed simply by having a better location than its competitors, even though its cost and service quality may not be as good.

If a company uses the “wrong” manufacturing or service process, there will likely be a mismatch between what the customer wants and what operations can provide. For example, a job shop manufacturer that tries to make high-volume, standardized products at low cost will likely be at a competitive disadvange when compared to high-volume batch or line manufacturers.

2. Generally one would expect production lines to be upstream of the customization point in a supply chain because the focus would be on a standard product with minor customized parts. In contrast, in a job shop the production process would be downstream of the customization point because job shops are mainly focused around customized products and need high customer input to be able to determine what is required. 3. The customization point of these cups is after the initial white cup has been created. The white cup is generally just a standard cup that can be customized into anything the customer would want so companies would have large, standard stocks of these white cups upstream of the customization point waiting for customer input. After the customer contacts the company, it can customize the cups with any logos and colors and send them to the customers after the custom logos are added to the white cups. A white cup with a final process step of printing is likely a less expensive and more reactive supply chain design. 4. The Ford Mustang was originally produced on a production line. Nowadays, as these cars approach fifty years of age, what’s required to restore them to like new will differ greatly from one specific vehicle to the next. As such, a job shop process, characterized by highly-skilled, flexible workers, will be the preferred process choice. 5. Group technology resembles a batch process because it has dedicated personnel and equipment to make families or subfamilies of products with similar manufacturing requirements. Group technology processing is also like a production line because the cell is arranged to follow the dominant flow of activities for the product. A group technology process is able to make a work cell more efficient by grouping the product families together, but it does so at the expense of making the work cell less flexible. .

6. The main advantages of Web-based courses are their flexibility: Students can attend when it is convenient, and schools do not have to build and maintain physical classroom facilities. However, students in online courses may have fewer opportunities to engage directly with the instructor in an efficient manner. In a traditional class environment, the give and take between students and instructor can be very organic and lead to insights and examples that fall outside what the instructor had planned. A large lecture setting tends to steer an instructor to a limited set of presentation options–e.g., discussion and group activities can be difficult to manage with the sheer number of students and classroom layout. For the instructors, developing online courses requires considerable technical sophistication, especially as the richness of content (including online grading, presentations, etc.) becomes richer.

1. P&G’s adaptation of a business process oriented perspective in the mid-1990’s in the form of Streamlined Logistics provided the customers with one face for various P&G business sectors. This initiative gave customers efficiencies in procurement, accounts payable, pricing discounts, inbound delivery receiving, and customer service. Prior to the implementation of the Streamlined Logistics initiative, each of the businesses at P&G focused on themselves and had their own logistics and sales policies; thus, they were blind to the policies of the other business groups and problems faced by the external customers. The P&G Logistics team’s shifting the focus from internal to external resulted in the necessary changes and improved the profitability for both P&G and its customers.

2. An example where focusing on cycle time might hurt other important measures of performance is a fast food resturant buying more fryers and having them constantly running to ensure food is always ready for the customer. This could eliminate cycle time of waiting for food to be prepared or finish cooking, but the cost of more, constantly running fryers is considerable and the quality of the food sitting after it leaves the fryer is less than optimal as well.

3. The course registration at most universities would be considered a mass customization process. This is because there is controlled variation in the classes that students may choose, based on their degree programs.

4. QUALITY

COST

TIME

FLEXIBILITY

Productivity

+/-

Efficiency

+/-

Cycle time

+/-

Using performance measures to evaluate processes is a great way to identify potential strengths and weaknesses in manufacturing processes. By using the performance measures of productivity, efficiency, and cycle time, a company should be able to identify great and poor levels of performance and use these measures as ways to develop employees and make important management decisions. However, by just following the aforementioned measures, the company can miss other important factors within processes.

1. As per IATA, the cost of a lost bag to an airline is estimated at $100 per bag. This is the quality failure cost related to baggage-handling process. To help resolve the quality failures, Delta made an investment of $100 million at the Atlanta Airport. It also incurred costs of quality in training employees on the new system, costs of inspection of the system, and general equipment maintenance as well. Delta can likely justify spending $100 million in Atlanta. Atlanta is a major hub, and the system will last Delta many years. 2. The fact that quality is defined using the words needs and deficiencies is why two people can perceive the same product or service as having different quality levels. Needs differ from consumer to consumer, and the definition of what is deficient changes between consumers as well. Since consumers define quality differently, it is critical for businesses to “know their customer” and find what they are looking for in the products so that they may deliver on the needs of the majority of their users.

3. In this case, both sides can be right because of the dichotomy of the definition of quality. The value-based perspective on quality is about satisfying the end user’s needs, and according to the plaintiff the need for the door to hold up under stress was not met. However, the conformance perspective measures the product against pre-established standards, and the manufacturer met the government requirements which satisfy a definition of quality. 4. Statistical quality control is primarily focused on making sure that a business’s current processes are meeting predetermined specifications. According to this definition, statistical quality control would be used during the control phase of DMAIC where the focus is on monitoring the current process using statistical data analysis.

5. This occurrence must be investigated further before a potential problem gets out of hand. The caveat to this position is that a lower level of variability is desirable, so if this reduced variability is legitimate, there would be strong motivation to pursue its repeatability and recalculate control limits.

1. Operations and supply chain environments characterized by standardized products or services will naturally have an easier time planning capacity because requirements are relatively well-known. For example, a manufacturer producing food processors knows exactly what steps are required, what parts are needed, and how much labor/machine time should be required. In contrast, a job shop literally cannot compare the capacity requirements of one job to the next. 2. A fire station most likely would follow a lead strategy because it would allow them enough capacity to meet all distress calls, even during spikes in demand. Driver’s license testing centers, like most government agencies, would operate under a lag strategy. The lag strategy would allow the agency to have the lowest cost possible, but at the cost of having long lines. 3. A start-up company would benefit more from a “virtual -supply chain” because they tend to have fewer resources than a more established company. The risks associated with a “virtual supply chain” are that a company is highly dependent on its partners, and can be left “high and dry” if business conditions shift and the partners no longer need to do business with them. 4.

Since customers arrive randomly, it is impossible to have checkout clerks busy 100% of the time without waiting times becoming inordinately long. The queuing formulas in the chapter support this. The busier the checkout clerks are with customers, the more likely that the waiting line will grow and customers would become unhappy with the wait.

5. Learning, productivity, and effective capacity are all interrelated. As employees learn within the organization, their productivity will improve and this causes an increase in the effective capacity of the organization. It is wise to use learning curves to anticipate future resource requirements. Learning curves allow the organization to predict the fewest number of inputs needed to maximize outputs, and they also allow the organization to make educated inferences of capacity decisions without overestimating capacity. However, learning curves must be thought of only as a guide, because usually learning improvements do not occur on a smooth curve. Furthermore, there is also a limit on the learning curve effect and managers can sometimes underestimate what they need as well. 6. The manufacturer would need the customer demand to double in order to see the throughput for the system to double. By doubling manufacturing capacity without a demand increase they would eventually accumulate inventory. Other constraining factors for the system would be the amount of raw material the supplier could provide, and the company would also have to invest large amounts of capital in employees to be able to properly run the increased capacity of the manufacturing step.

1. Constant service times eliminate one of the two key sources of variability in the queuing model, the other being time between arrivals. As a result, we should expect constant service times to result in improved performance, all things being equal. As an example, suppose you arrive at the bank with three people ahead of you. If the service time is a constant 2 minutes, you know you will wait about 6 minutes (depending on how long the first person has been “in service”). On the other hand, if the service times vary, you could be in for a shorter, or much longer, time.

2. A supply chain where multiple manufacturers take turns processing a particular product suggests multiple phases. Hence, Figure 6S.3 best represents this environment.

3. All simulation modeling does is capture, in a convenient and easy-to-analyze manner, the environment one intends to model. If the decision-maker builds a model of a less-than-desirable environment—for example, one teller trying to service 100 customers an hour—then the simulation results will reflect that environment. That said, simulation models can help guide decision-makers to better solutions via “what if” analyses.

1. The cafeteria services available at universities are often outsourced because they are not a core competency of the university. Thus, the university (and the students) can most likely get better quality and value by outsourcing these services to a provider for whom it is a core competency. By outsourcing, the university faces a low investment risk that comes with high strategic flexibility and it will realize an improved cash flow. Since the university is buying cafeteria services, it is working in the routine quadrant. 2. Negotiation is a more costly and interactive approach to supplier selection than competitive bidding; however, there are a few conditions that make it a more viable selection tool. Negotiation should be used when the item is new or complex, there is a wide range of performance factors, the buyer requires supplier input for development, and/or the supplier cannot determine risks or costs without additional input from the buyer. The main use for negotiation is to engage supplier to develop a new or complex product, especially when there is no clear “best” supplier choice available. 3. Information systems have already eliminated many of the traditional clerical tasks that purchasing professionals had to do. Orders can be made online, planning and control systems can generate orders automatically, and information systems can instantly forward component requirements to suppliers, minimizing the need for purchasing intervention. It is a good time to join the purchasing profession because companies are becoming more dependent on suppliers. Advanced information systems can automate some tasks, but purchasers are still needed to make initial contact, create substantive relationships, and negotiate terms and agreements with suppliers. 4. Spend analysis can be used to both define the size of the opportunity (the “D” in DMAIC) and as a way to gather detailed data (the “M” in DMAIC) regarding where money is being spent, whom it is being spent with, etc.

1. The view that logistics is just trucking and warehousing is wrong because these are only two of the key decision areas that make up logistics. Logistics is the part of the supply chain that plans, implements, and controls the efficient, effective flows and storage of goods and services between the point of order and the point of consumption in order to meet the customers’ requirements. In order to control these flows of goods and services, companies need to be efficient in transportation, warehousing, material handling, packaging, inventory management, and information systems. Without properly integrating all of the aforementioned components of logistics management, the rest of the supply chain would experience problems such as service interruptions, excessive expenditures, missed deadlines and damaged goods. 2. It is a false claim that warehousing is inconsistent with efforts to minimize inventory levels through the supply chain. When warehousing is leveraged correctly, such as inventory pooling, a company can avoid having wasteful inventory in each store by having a safety stock in a central location. By having a central location to hold stock, firms can limit lead times to the customer, have extra stock for spikes in demand, and support multiple locations from a single location. 3. A firm can be a part of the logistics systems industry without touching the product. Examples include software companies that design and support logistics information systems and “online” retailers who depend on third-party carriers to deliver products from manufacturers to customers. 4. Landed costs become more important for firms that participate in international logistics because these firms will incur multiple types of costs throughout their supply chain. Landed costs include the product cost plus all costs driven by activities including: transportation, warehousing, handling, and customs fees among others. International supply chains will have to consider landed costs in the forms of customs fees, and they need to pay a freight forwarder to be an intermediary between the shipping organization and the actual carrier. 5. Consider the wide range of business activities that fall under the umbrella of logistics: transportation, warehousing, material handling, packaging, inventory management, and logistics information systems. As with other operations areas, logistics involves choice. If a company does not have a guiding strategy to ensure that these pieces fit together and support the business strategy, it’s highly unlikely that the firm will make consistent choices across all these complex areas. 6. Logistics can be an area of core competency for a company. A prime example is that of UPS. UPS’s business slogan at one time was “We love logistics,” and their business strategy is to be the one-stop shop of logistics for their customers. They do all of the necessary logistic functions, including warehousing, shipping, tracking, material handling, and inventory management. It makes sense for a company to have logistics as a core competency because it is an area of the .

supply chain where a lot of money is spent, thus a lot of money could be saved if it is managed skillfully.

1. Causal modeling is likely to be the best approach, because factors other than time—such as economic conditions, demand levels, political unrest, etc.—can be used to forecast fuel prices. 2. Time series forecasting techniques are not terribly well-suited to developing forecasts for multiple periods into the future because they have built-in mechanisms to incorporate past demand for future forecasts. Mathematically, to make time series models work past one period, one would have to use the forecast in place of actual demand numbers. As a result, the forecast would not change, or would go up or down by the trend estimate. 3. The advantage of having computer-based forecasting packages lies primarily in the fact that they can quickly develop and evaluate forecasts for thousands of products. These packages can also use tracking criteria to flag a poor forecast model and automatically start a search or a new forecasting model. However, using a computer-based forecast model can be risky because the computer only takes into account numbers and misses things that people can see such as whether something is quickly going out of style or whether a new alternative has been created and is unaccounted for in previous demand. 4. Linear regression to develop a time series forecast is different from a causal because the independent variable, or x, changes between the two forecasting types. In a time series, the independent variable is always time. For causal models, the linear regression independent variable is something that causes change other than time. 5.

Forecasting is very important for firms because they depend on forecasts as an input to many planning activities. But firms also need to address the organizational issues surrounding forecasting—for example, how will we share data and who will be responsible for generating the forecasts? This is where approaches like CPFR come into play. CPFR focuses on collaboration, co-planning, and data sharing across supply chain partners.

1. The process of developing the sales and operations plan is as important as the final numbers because, as Richard Ling said, “S&OP is a people process supported by information.” The process of compiling the information from all of the functional areas (operations, marketing, sales, finance, and others) of the company involves making many different plans that often require trade-offs between the areas until a final plan is agreed upon. If input from all areas is not equally considered and analyzed in the process of coming up with the final plan, then the final numbers can be far off the mark. 2. Strategic planning involves the top managers in the organization. They make decisions that impact actions potentially years in the future. Detailed planning happens at much lower levels and really involves decisions regarding actions that will take place within days or even hours. S&OP addresses an intermediate time horizon, typically 12 to 24 months. In this sense, it acts as a link between higher-level strategic plans and lower-level detailed planning. 3. Level production plans are best suited to environments in which changing the production level is almost impossible or extremely costly and cost of holding inventory is relatively low. Chase production is best for companies that cannot afford to hold inventory and the production levels change constantly due to low costs in changing productions. Companies need to choose the plan that best suits them based on the cost to hold inventory and the cost to change production levels almost instantly. 4. Services do not have products in inventory, so they need to be concerned with matching capacity with demand in each period. Services are effectively limited to following a form of chase production because they are flexible enough to meet demand and they do not have the ability to hold any inventory. Service companies’ two main options for aligning resources with demand are to make sales match capacity and/or to make capacity (workforce) match sales. If a service company can effectivly match a chase production strategy to their resource alignment options, they should be able to maximize their S&OP. 5. It is important to update the sales and operations plan regularly with a rolling time horizon .

approach because doing so will update the current plan for the future with the most recent values. A rolling time horizon helps the S&OP keep up-to-date with current trends and demand so that management can make the most informed decisions with the current valuable information. 6. Superior S&OP can provide a firm with a competitive advantage because, done correctly, the result is a better use of resources and consistent decisions across the key functional areas of operations, marketing, and finance. In effect, everyone is working from the “same numbers.” 7.

Two key advantages of coodinating a firm’s S&OP with key supply chain partners are 1) it helps eliminate uncertainty by combining forecasts, and 2) the information flow between suppliers helps limit the disruption of flow of goods within the supply chain. One potential drawback is that much of the information shared may be proprietary. As a result, trust is necessary for such sharing of information to take place.

1. It is not true that any inventory is a sign of waste because companies need to have some inventory so goods are available to customers when they want/need them. Do you want to arrive at a hospital, needing blood, only to hear that the hospital has implemented a “zero inventory” policy? That said, there does need to be a balance between ensuring demand is met and holding inventory. Holding too much inventory ties up capital, and companies lose flexibility in the chain. Managers need to make the customers happy by having goods in stock, but they do not want to have so much inventory that it costs too much to hold. 2. An inventory driver is something that causes companies to hold more inventory than they usually would. Controllable inventory drivers, as the name suggests, are those that can be managed or addressed by firm actions. For example, improving manufacturing flexiblity can reduce the mismatch between downstream demand requirements and manufacturing’s capability, thereby reducing the need for cycle stock. On the other hand, some drivers, such as demand uncertainty, may or may not be controllable. 3. Independent demand inventory are items whose demand is determined by outside parties (typically the final customer). Examples include items A, C, and D in the list. Dependent demand inventory is under “complete control” of the company because the demand level is directly tied to the planned production of another item. Items B and E are good examples of demand dependent items—how many bicycle wheels or hamburger buns are needed depends completely on how many bicycles or hambergers are produced. 4. A good reason to push inventory downstream is to have inventory positioned where customers need it. A con of having the inventory downstream is that it is often very difficult to “reverse” the supply chain and reposition goods to a new point, and a product positioned at a decentralized demand point is inherently less flexible than the same product positioned at a centralized demand point. Modular designs help break the process down into chunks, making it easier to pull together the key pieces to make a final configuration. This allows lower inventory costs and also provides more final product flexibilty. .

5. According to the EOQ, lowering ordering cost would result in lower order quantities and hence lower inventory levels. With regard to the ROP formula, reducing variability in demand and/or lead times, as well as reducing average lead times, would result in lower safety stock levels. 6. Lowering the ordering costs would result in a lower EOQ. Stabilizing the demand level means lower demand variability and therefore, less safety stock needed for a given service level. Shrinking lead times would have a similar impact on safety stock. Finally, assigning a higher holding cost would result in lower EOQ values.

1. This is not true because S&OP helps firms plan operations over a multi-month horizon based on forecasted demand, and master scheduling is planning that matches output to actual orders. They are similar because they both consider demand, production, and ending inventory. They are different because S&OP are forecasts for the future while master scheduling deals with the real and current demand/output. Master scheduling also gives information on booked orders and available to promise units, which S&OP cannot forecast. It would be very hard to do a master schedule without S&OP planning because S&OP planning provides targets that guide tactical decisions such as workforce levels, cash needs, and storage requirements used for master scheduling. 2. Master scheduling must be done first, because it “kicks off” the material requirements. The MRP really translates the master production schedule into planned orders for actual parts and components. Without the master schedule there would not be enough information to - make competent and factbased material requirements planning. 3. Forecasting is at the heart of planning and control systems because without effective forecasting everything else will be incorrect. A company can have strong planning efforts after forecasting, but if the forecast is significantly off, the information that goes through each phase of the planning will be off and will create either massive shortages or over-production. 4. MRP nervousness refers to the observation that any change, even a small one, in the requirements for items at the top of the bill can have drastic effects on items further down the bill. As you fall short of parts at the top, you cannot create more parts as you go down the bill, and at the bottom you have massive amounts of shortages. MRP nervousness can affect DRP systems as well because they use MRP-style logic to feed accurate demand information into the master schedule. 5. Many companies do an inadequate job of using master scheduling, MRP, and DRP planning because they take shortcuts in preparation or they lack knowledge of how to use them correctly. There has to be an organizational culture and discipline that causes managers to require the proper use of these tools to maximize the effectivness of the supply chain. Employees must be required by managers to do the work before it becomes second nature for them to do it. .

6. It is good to have a formal master scheduling process because it ensures uniformity in the calculation and results no matter who does the scheduling. If firms do not follow some of the basic rules of scheduling, there would be a disconnect between the supply chain, sales, marketing, and finance, which would likely result chaos among these units. 7. Master scheduling, MRP, and DRP must be used to coordinate activity up and down the supply chain so that everything - promised to the customers is delivered to the customers. You want to use the master schedule to know what you can promise your customers in terms of product availability. You need MRP and DRP to tell suppliers what you need and the quantity to meet customer demands, and you need suppliers to tell you their capabilities and whether or not they can meet your demands.

1. An information flow focuses on “what” information is being moved, while an information “system” is concerned with the “how.” For example, kanban (Chapter 13) is a type of information system that, simlilar to MRP (another type of information system), helps manufacturers determine when to produce parts. Information systems do not have to be computerized—they can be paper-based or even communicated verbally. 2. An argument can be made for either view, although most practitioners suggest tackling routine decision making and transactional requirements first. For one thing, they are easier to do and provide immediate payoffs. For another, these systems provide data that can be fed into higher-level planning systems. 3. Answers will vary. While many of the features are similar, the differences between manufacturing and service operations dictate some differences between system capabilities.

1. Necessary transportation is something that adds value to a good or service like a delivery from UPS or the delivery of a pizza. Unnecessary transportation does not add any value for the final customer and adds costs and increased damage risk. For example, moving a product back and forth between warehouses due to poor inventory planning would be an example of unnecessary transportation. 2. Waiting is a form of waste, but there are cases where waiting can actually make life easier for the consumer. An inbound call center can be run more economically if the center is capable of answering all calls on the first ring. If the center has that many representatives, they will be grossly underutilized and the company (and ultimately the customer) will be paying for much idle time. 3. Lean and quality management are similar in many ways, but they have differences as well. Both have a focus on customers, continuous improvement, and employee empowerment, but at their core, there is a fundamental difference. In quality management the focus is on what is important to customers, while lean is focused on eliminating waste and improving productivity for a better use of resources. 4. A planning tool is used to forecast what will be needed in the future, while a kanban is a control mechanism that is used to control inventory in a system. Example 13.4 illustrates that the planning and completion of work center A controls the flow of the metal through the system in work center B. MRP and kanban can be used together to anticipate changes in planned order quantities and then use that plan to recalculate the number of kanbans needed. 5. A firm’s suppliers could improve lean efforts by allowing the firm to hold lower stock or lowering lead times for goods. They can undermine lean efforts by requiring a firm to take all of their stock when it is finished -and they can have longer lead times that can cause firms to have a larger inventory and safety stock. In the Porsche example, Porsche took steps to fine-tune cooperation with suppliers to ensure factories received parts just when they were needed on the assembly line, a method that’s been widely copied in the automotive industry. By working with their suppliers on holding stock and/or manufacturing in a JIT fashion, they were able to slim down their supply chain and inventory drastically.

1. There is a wealth of information on www.pmi.org for project managers to choose from, including: blog writings from other professionals, professional articles, videos, case studies, and more. The Project Management Professional, Certified Associate in Project Management, Program Management Professional, PMI Scheduing Professional, and PMI Risk Management Professional certifications are available. When project managers come into a project or situation, they coordinate and direct the work in an effort to ensure that it is finished on time and correctly. 2. Project management skills are likely most important in businesses where projects account for the bulk of the business, for example, in construction firms or software development. Businesses that would place less value on project management skills would be ones that focus on routine activities such as a restaurant or retail store, although even these businesses would have projects occuring now and then. Project management skills are good to have for any job because they help multi-task and complete things on time, but they are especially important for firms whose business is primarily project based. 3. Network-based approaches are better than Gantt charts in that they show precedence relationships and Gantt charts do not. If a project has dozens or hundreds of activities, you need to know precedence relationships to see how crashes or delays will affect the overall project timeline. With network-based approaches, you can visually see the linkages between the activities. Gantt charts are preferable when there are only a handful of steps in the project. 4. It is important for network diagrams to be revised because they are similar to forecasts by nature. They are predictions of what should happen, but unpredictable delays may occur or sometimes things get finished more quickly. As the project goes on and the timeline changes, revising the diagram allows managers to make decisions on whether to crash during the project to meet deadlines due to delays.

1. Parts standardization is focused on using similar parts across different products to reduce part/supplier proliferation. This helps with repeatability, product costs, testability, and serviceability. Having the same parts from the same suppliers will offer volume discounts to save costs. It will make servicing easier because there is only one part to worry about, and testability/repeatability will be easier since you are comparing the same parts, apples to apples. Modular architecture focuses on having welldefined chunks and functions of product design. This helps with the repeatability, testability, and matching design with existing capabilities because the well-defined functions help engineers repeat and test the products the same every time, and the definitions will help create designs that match existing capabilities. 2. The advantages of concurrent engineering over sequential engineering are: shortens development times, forces teams to agree and stick to process characteristics early in development, and forces communication between all groups so that issues can be worked out together. Sequential development may be preferable if there is no general agreement on the characteristics of the new product at the beginning of the process. If this is the case, teams will need to create consensus as they go through each process step one-by-one. 3. It is important to meet the customers’ needs in the dimensions of cost, design, capabilities, and serviceability because all of these impact the consumer directly. It is more important for the process to be repeatable, testable, and to have good volumes for the firm because it is in these dimensions that the company saves money and makes a profit. If the firm has to cut out a little part of the good to save a lot of money it may be necessary to do, even at the expense of the consumers’ happiness. There are situations where this happens. For instance, consumers may want their good to perform a complex function, but if it makes the good harder to service, raises the price drastically, and/or changes the design significantly, then the firm may not respond to consumer pressure. 4. It is important to consider customers early in the development process because customers are ultimately going to decide if the good is a success and buy it. You want to meet as many of the customers’ needs as possible with the good, so you know what they want when you make it. If you do .

not find these needs early and incorporate them into the initial design, then you risk having to change design and functionality later at a huge cost. 5. The latest version of an existing product would be better suited for concurrent engineering. The new product has guidelines already established, which makes it easier for phases to overlap without leaving out any large details. The new technology would require each development team to inspect and design their portion of the product so that everything has been deliberately created and looked at before the product is launched. 6. Some benefits of supplier inclusion are gaining a supplier’s insight into the development process, allowing comparisons of proposed production requirements with a supplier’s existing capabilities, and allowing a supplier to begin preproduction work early. The risks are that if you give suppliers the blueprint of your product, you never know if that information could be stolen or given to a competitor. You also are risking losing competition for parts because if you include the supplier in the development then you are really committing to them - for the foreseeable future.

A Simple Transformation Process Diagram of a Car Repair Shop: Inputs Cars Parts

Transformation Process Diagnosis Repair Installation Testing Tools Knowledge Equipment Labor

Outputs Repaired Cars Satisfied Customers

The target audiences of the websites of the professional organizations listed in this chapter are employees working in operations and supply chain positions who want to continue to learn from the best practices of other organizations and add to their ability to excel in this challenging field. There are organizations focused on many different areas of operations and supply chain management including purchasing and logistics. Some of the careers listed in the web sites that are mentioned in the chapter are analyst, customer service manager, international logistics manager, production manager, sourcing manager, and systems support manager. All of these positions sound appealing. (Answers will vary)

Question 1.) Upstream Suppliers 2nd-Tier Suppliers 1st-Tier Suppliers Leap Frog DuPont Co. (Tyvek) Capable Toys Leap Frog Microchip Suppliers Tool Manufacturers Plastic Resin Suppliers Speaker Suppliers Touch-Membrane Suppliers

Downstream Suppliers Distributors Air Freight Carriers Fast Boat Carriers Other Carriers

Question 2.) The data that ultimately led to LeapFrog's decision to increase production levels of the LittleTouch LeapPads were the sales numbers showing 360 of the product during it's introductory weekend. The data came from retailers who shared their real-time sales data with their suppliers in order to better manage customer demand. In order to best meet the demand of the customers during the holiday season LeapFrog started talking with Capable Toys about increasing production within days of the initial sales numbers.

Question 3.) The parts of the production process that limited production at Capable Toys were the sets of tools that created the molded plastic parts. Initially Capable Toys only had two sets of tools that were capable of producing 3,500 units per day. Capable Toys reacted to the increase in demand by designing and building additional sets of tools, each allowing faster production and lowered numbers of defects than the originals.

Question 4.) Some of the material sourcing challenges facing LeapFrog and Capable Toys included the limited supply of microchips, shortage of Tyvek paper, and the need for additional plastic resin. They were able to meet these challenges by sourcing from additional partners, finding additional channels of supply, and increasing orders from existing suppliers.

Question 5.) Because of the urgency of getting the toys to the retailers as quickly as possible, LeapFrog turned to air freight as well as express ships. These methods shortened the time to market for the LittleTouch LeapPads and helped establish the product line in the market but they had the weakness of being very expensive and reducing the profit margin. If LeapFrog would have been able to produce the extra units in August instead of December, then they may have been able to use more standard and less expensive ocean shipping methods.

Question 6.) Agility is defined as the ability to quickly recalculate plans in the face of market, demand, and supply volatility. Leapfrog and Capable Toys used their information systems, flexible manufacturing capability, and cooperation of supply chain p In house design tems developed new molds, suppliers found additional sources for necessary components, and the logistics fu used faster delivery modes to get their products in the hands of their customers.

Downstream Suppliers Retailers Target Kmart Toys "R" Us Wal-Mart

he LittleTouch LeapPads were the ta came from retailers who shared mand. In order to best meet the apable Toys about increasing

e sets of tools that created the able of producing 3,500 units per ditional sets of tools, each allowing

ed the limited supply of y were able to meet these y, and increasing orders from

apFrog turned to air freight as well LeapPads and helped establish nd reducing the profit margin. If ember, then they may have been

and, and supply volatility. capability, and cooperation of supply chain partners to respond to the necessary components, and the logistics function

DIMENSION Fuel economy Reliability Speed and handling Aesthetics After-sales support Purchase price Totals:

IMPORTANCE VALUE INDEX IMPORTANCE HONDA BIZZARINI HONDA BIZZARRINI TO YOU ENIGMA BOOSTER ENIGMA BOOSTER 3 5 2 15 6 5 5 2 25 10 4 2 5 8 20 4 2 5 8 20 2 4 4 8 8 4 4 1 16 4 80 68

The Honda Enigma provides me with the greatest value as its total value index is 80 compared to 68 for the Bizzarini Booster.

a.) 36 hrs

$15

99%

6 hrs 98% 48 hrs $20 8 hrs

72 hrs

95%

9 hrs

$30

Order Qualifiers Order Winners Pick up shipments Deliver shipments Cost per 100 lbs. % of shipments in less than 8 in 72 hours or less shipped that arrive hours. undamaged McAdoo

Klooless

Big Al

b.) McAdoo is most likely to win the business because they are the only supplier that met both order qualifiers. c.) Big Al is the highest performing supplier for every category except for pick up time. If they are able to lower their pick up time to meet the order qualifier they will likely win the business. d.) Klooless has poor competitive position. They do not meet the qualifier for pickup in less than 8 hours, they barely meet the qualifier for delivery time, and they perform poorest of the three competitors in the two order winner categories.

a.) Increasing the conformance quality to above the qualifier level will allow Supplier B to compete for the business. Since Supplier B is better than Supplier A in 2 of the 3 categories, Supplier B will likely win the business if it is able to meet the qualifier. However, it still ultimately depends on how the various customers value the different order winners.

b.) Supplier A should decrease their cost to $18 per liter by increasing the minimum order quantity to 80 liters. Doing this will result in Supplier A being the leader in 2 of the 3 order winner categories and will likely win the business. If possible, Supplier A may want to offer the choice of smaller order sizes vs. lower per liter price to each potential customer. (Answers can vary).

Calculating the Value Index for Two Alternative Suppliers Performance: 1 = "poor" to 5 = "excellent" Importance: 1 = "completely unimportant" to 5 = "critical"

Performance quality Conformance quality Delivery reliability Delivery speed Cost Mix flexibility Volume flexibility

Importance 3 3 3 3 3 3 3

Performance Supplier 1 Supplier 2 4 3 5 4 5 4 1 3 3 5 2 1 4 1 Totals:

Value Index Supplier 1 Supplier 2 12 9 15 12 15 12 3 9 9 15 6 3 12 3 72 63

Question 1.) In 2011, Netlfix changed their focus from physical distribution of DVDs to direct streaming. Pre2011, they had the logistics capability to achieve one-day delivery and could spur demand for existing titles by recommending them based on customers' revealed preferences. In short, Netflix was delivering service (entertainment) via a tangible item (the disc). Post-2011, Netflix decoupled the intangible service from the disc by emphasizing diital streaming. This lowered physical distribution costs dramatically. Question 2.) Order winners and qualifiers for Netflix likely include availability of desired content and speed of delivery for both pre and post-2011. With the new capability of digital streaming services, the standard for delivery speed has changed dramatically for many customers. Customers on the wrong side of the digital divide will still focus on delivery of discs, as may customers with more vintage tastes that are less likely to find their favorite movies and shows digitally. Customers that seek more recent media would consider the agreements Netflix signs with major production studios paramount. Question 3.) Netflix may choose to abandon physical distribution, but a significant market still exists for those that need delivery of discs via USPS. In some cases, these customers do not have sufficient bandwidth to support streaming of content. Other customers may favor discs over digital because discs often have special features, e.g., director's commentary, deleted scenes, etc., that are not available with a streaming service. This is a decision that Netflix should revisit periodically based on potential revenues and expenses as they perceive shifts in the market's taste.

a.) Available Production Time: Required Output Rate: Task Time per Unit: Takt Time: Min Number of Workstations:

480 50 45 9.6 5

Minutes Boats Minutes Minutes per Boat Workstations

b.) Yes, because the longest task time (4 minutes) is less than the takt time. The takt time is equal to the highest allowable cycle time in order to meet the required output rate.

Number of Workstations: Cycle Time: Total Task Time: Idle Time: Percent Idle Time: Efficiency Delay:

4 50 170 30 15% 85%

Seconds Seconds Seconds

Available Production Time: Required Output Rate: Task Time per Unit: Longest Individual Task Time: Takt Time: Maximum Output Per Day:

28800 50 360 50 576 576

Seconds Coolers per 8-hour day Seconds Seconds Seconds per cooler Coolers

Because the longest task time is 50 seconds, the cycle time could be as low as 50 seconds, allowing 576 coolers to be produced in a 28800 second day.

a.) A

J H

K G

Task Time per Unit: Takt Time: Min Number of Workstations:

15.65 4 4

Minutes Minutes per Server Workstations

Workstation 2 Task Time E 1.7 G 0.7

Workstation 3 Task Time H 1.7 I 1.2

Workstation 4 Task Time K 2.7

Workstation 5 Task Time J 2.3 L 1.5

Total:

b.) Workstation 1 Task Time A 2.9 B 0.2 D 0.4 C 0.25 F 0.1 Total: 3.85

2.4

2.9

c.) The "largest eligible task" rule results in a solution with 5 workstations. Cycle Time: 3.85 Minutes Idle Time: 3.6 Minutes

2.7

3.8

a.) Available Production Time: Required Output Rate: Task Time per Unit: Takt Time: Min Number of Workstations:

480 150 8.3 3.2 3

Minutes Returns Minutes Minutes per Return Workstations

Workstation 1 Task Time A 0.75 B 1.25

Workstation 2 Task Time C 2.5 D 0.5

Workstation 3 Task Time E 0.3

Workstation 4 Task Time F 3

Total:

b.)

Cycle Time: Idle Time: Percent Idle Time: Efficiency Delay:

3 Minutes 3.7 Minutes 31% 69%

c.) Minimum Cycle Time: Maximum Daily Output:

3 Minutes 160 Returns

0.3

a.) A

Available Production Time: Required Output Rate: Task Time per Unit: Takt Time: Min Number of Workstations:

28800 100 713 288 3

Seconds Pumps a day Seconds Seconds per Pump Workstations

b.) Workstation 1 Workstation 2 Workstation 3 Task Time Task Time Task Time B 150 A 100 F 84 D 120 C 93 G 65 E 86 H 15

Total:

270

Total:

279

Total:

164

c.) The "largest eligible task" rule results in a solution with 3 workstations. Cycle Time: 279 Seconds Idle Time: 124 Seconds Percent Idle Time: 15% d.) Because the longest single task time (and thus the lowest single cycle time) is 150 seconds, it is not possible for a single work cell to produce 200 pumps per day. Producing 200 pumps per day would require a takt time of 144 seconds and a cycle time of equal to or lower than the takt time. It would be possible to produce 200 pumps per day with an additional work cell (duplicating the existing work cell's tasks).

a.) A

Available Production Time: Required Output Rate: Task Time per Unit: Takt Time: Min Number of Workstations:

60 30 7.65 2 4

Minutes Applications Minutes Minutes Workstations

b.) Workstation 1 Task Time A 1.2

Total: Idle Time:

1.2 0.8

Workstation 2 Task Time B 1 C 0.65

Workstation 3 Task Time E 1.3

Workstation 4 Task Time D 1.1 G 0.8

Workstation 5 Task Time F 0.7 H 0.9

Total:

1.65 0.35

1.3 0.7

1.9 0.1

c.) The "largest eligible task" rule results in a solution with 5 workstations. Cycle Time: 1.9 Minutes Idle Time: 1.85 Minutes Percent Idle Time: 19% Efficiency Delay: 81% d.) The longest single task time (and thus the lowest single cycle time) is 1.3 minutes. This translates into 46 applications per hour.

1.6 0.4

Layout 1:

Trips Made Per Day: 1 2 10 3 5 4 30

2 60 40

3 50

Total Distance Traveled: Trips Distance Dept 1 - 2 10 40 Dept 1 - 3 5 45 Dept 1 - 4 30 20 Dept 2 - 3 60 20 Dept 2 - 4 40 45 Dept 3 - 4 50 40 Grand Total:

Total 400 225 600 1200 1800 2000 6225

Trips Made Per Day: 1 2 10 3 5 4 30

3 50

Distance: Short Long Diagonal

Layout 2:

2 60 40

Total Distance Traveled: Trips Distance Dept 1 - 2 10 20 Dept 1 - 3 5 45 Dept 1 - 4 30 40 Dept 2 - 3 60 40 Dept 2 - 4 40 45 Dept 3 - 4 50 20 Grand Total:

Total 200 225 1200 2400 1800 1000 6825

The maximum number of arrangements is 24. Of the two alternatives shown, layout 1 is the better choice because of the lower average total distance traveled.

20 40 45

Departments: 1 Waiting 2 Reception 3 Records and Staff Lounge 4 Examination 5 Outpatient Surgery 6 Physical Therapy Trips Made Per Day: 1 2 100 3 0 4 35 5 15 6 50

Distance: Adjoining Separated Diagonal Long Diag.

15 30 25 40

Layout: 2 150 5 5 10

3 10 10 15

4 5 40

5 0

a.) Given that Dr. Douvas wants Reception assigned to area A, there are 120 possible arrangements. b.) 2

Total Distance Traveled: Trips Distance Dept 1 - 2 100 15 Dept 1 - 3 0 25 Dept 1 - 4 35 25 Dept 1 - 5 15 15 Dept 1 - 6 50 15 Dept 2 - 3 150 15 Dept 2 - 4 5 40 Dept 2 - 5 5 30 Dept 2 - 6 10 25 Dept 3 - 4 10 30 Dept 3 - 5 10 40 Dept 3 - 6 15 15 Dept 4 - 5 5 15 Dept 4 - 6 40 15 Dept 5 - 6 0 25 Grand Total:

Total 1500 0 875 225 750 2250 200 150 250 300 400 225 75 600 0 7800

c.) I switched department 1 (Waiting) with 5 (Outpatient Surgery) but there was an increase in the total distance traveled. 7800 is the optimal solution.

Layout:

Distance: A B

S C

B C D E

A 14 8 14 18

B 8 20 14

C 8 8

D 14

2 52 5 56 15

3 17 28 57

4 25 3

E Trips Made Per Day: 1 2 23 3 24 4 13 5 21 6 60 Potential Layout: 1 2

S 6

4 It is difficult to develop a potential layout as there are 6 departments and only 5 areas for them to occupy. It will be important to know which two departments can fit into a single space and if that can only happen within one of the possible spaces. Also, if there is a "reception" department, there may be a restriction on that department needing the central space where the stairs are located.

5 42

Question 1.) Through 2017, LWT appeared to be using a make-to-stock manufacturing process. There was very little customization offered. Customers were allowed to chose from one of the few available designs and the few available sizes. The point of customization was just before distribution, where the shutters waited in the warehouse. Question 2.) Prior to 2018, LWT's service package was primarily physical activities (manufacturing shutters and fulfilling orders from stock), lower customization (customers offered only a few styles and sizes), and low degree of customer contact (customers interacted with LWT only through the design retailers. Question 3.) To support the changes proposed by Chuck Keown, LWT will need to have a make-to-order manufacturing process. They will be able to offer a much higher level of customization as customers will be able to build to any size and using any of the designed components. The point of customization will be between sourcing materials and fabrication. Question 4.) After the changes proposed by Chuck Keown, the service package of LWT will include more intangible activities (knowledge of designing components, matching materials well, managing sales people), a much higher degree of customization (customers able to order any size needed, with any number of shutters ordered), and a much higher customer contact (customers able to order directly from LWT through the website and catalog). New managerial challenges will be hiring and training sales staff, working with IT to get a website designed, hosted, and supported, creating the manufacturing capability to meet customer orders quickly and accurately, maintaining high quality of products while producing much lower volumes of much more differentiated Question 5.) Many things must happen in order to accomplish the changes that Chuck Keown envisions. These include; engineering, procuring, and setting up new manufacturing equipment capable of handling low volume - high variability of products, recruiting and hiring a different class of employees (customer sales) than LWT has previously worked with, management must prepare for a different set of day-to-day issues (customer contacts) that they have not experienced before, the current design retailers will need to be informed of the new business plan, LWT must hire skills needed to design a catalog and fulfill customer orders, and the IT department will need to include new skills of website management and support. This new business model will be more difficult to manage as the point of customization has been moved further upstream in the manufacturing process, creating more variability and an inherently less productive process

Part a

Customer Places Order

Attendant Gathers and Bags the Order

Attendant Takes the Order

Process Step Customer Places Order Attendant Takes the Order Attendant Gathers Food Attendant Takes the Money Customer Receives Food

Minimum Cycle Time (Seconds)

Longest Cycle Time (Seconds)

30 30 30

40 120 40

200

Total Cycle Time:

Attendant Takes the Money

Part b

Attendant (1) Takes the Money Customer Places Order

Customer Receives Food

Attendant (1) Takes the Order

Attendant (2) Gathers and Bags the Order

Process Step Customer Places Order Attendant Takes the Order One Attendant Gathers Food While Other Attendant Takes the Money Customer Receives Food Total Cycle Time:

Minimum Cycle Time (Seconds)

Longest Cycle Time (Seconds)

120

160

Potential problems that could arise by splitting the process across two individuals include introducing communication issues that cause some orders to be wrong, space constraints of two attendants working in the same space, and lower utilization while one attendant waits on the other to complete his or her task.

Customer Receives Food

a.) Customer downloads, completes & submits form (3-5 days)

Error on Form?

YES

Application waits 1 to 2 days

Agent Corrects Forms with Customer (5 - 30 Minutes)

Batch Waits for Monday (0 - 5 Days)

Loan Officers Process Loan (2 - 3 Days)

Customer is Advised of Final Decision

Rework will occur in this process whenever a customer is sent new forms to complete. This happens because whenever the customer returns the forms, they must be checked again for any issues. Delays in the process occur when the agent tries over 2 days to contact the customer, when waiting for mail to get back and forth between the customer and the lender, and when waiting for the Monday morning batch of applications to be taken to the officers. The impact on cycle times is a significant increase in the number of days for Faircloth to deliver a decision to the customer. Because of this, many customers may have already received a positive response from another lender and Faircloth will have lost their business. Customers may also be less likely to apply to Faircloth in the future because of the slow approval time.

b.) Recommended changes to the process would include an online application process that would check the application and not allow submission until all problems with the form were corrected. Sales representatives could be available for customers to call if they have trouble completing the form correctly. Submitted forms should be received directly by the loan officers electronically. The officers would take 2-3 days to make a decision and then customers would be notified. Using this process, total cycle time would be reduced to the 2-3 days it takes the loan officers to gather information from credit bureaus and make a decision. This would be a reduction of up to 19 days.

Need Initials

Need Initials NO

YES

Customer is Mailed New Forms and Mails Them back (5 - 7 Days)

a.)

Marci Jack

Hours 15 8

Pages 20 15

Productivity (pages/hour) 1.33 1.88

The output is the number of written report pages. The input is the number of hours spent on research and writing. This is a single-factor productivity measure. b.) The limitations of using productivity measures to evaluate their performance is that the quality of the work is not assessed, only the number of pages per hour. The instructor may use other measures including the depth of analysis, completeness of ideas, and level of writing.

WEEK 1 2 3 4 5 6

OUTPUT (IN UNITS) 1,850 1,361 2,122 2,638 2,599 2,867

LABOR PRODUCTIVITY HOURS (UNITS/HOUR) 200 9.25 150 9.07 150 14.15 250 10.55 250 10.40 300 9.56 AVERAGE: 10.50

Week 3 seems unusual as it is almost 40% higher than the average units/hour productivity level. There seems to be high variability in the production process.

YEAR 2012 2013 2014 2015 2016 2017

TOTAL SALES $4,790,000 $5,750,000 $6,900,000 $8,280,000 $9,930,000 $11,920,000

PHONE REP COSTS $200,000 $210,000 $221,000 $230,000 $245,000 $255,000

WEB SITE COSTS $50,000 $65,000 $85,000 $110,000 $145,000 $190,000 AVERAGE:

Part (a): Productivity (Sales/Phone Rep $) $23.95 $27.38 $31.22 $36.00 $40.53 $46.75 $34.30

a.) The productivity of each dollar spent on phone rep costs has increased each year during the six year period.

b.) The productivity of each dollar spent on web site costs has decreased each year. c.) The limitation of the single-factor productivity measures are that they assume there is a 1:1 relationship between the output and input of interest that can be managed. Considering just labor costs (phone reps) may be inappropriate, especially when labor costs could be driven down by investments elsewhere (e.g., web site). In this case, it is better to look at sales per total costs.

d.) The sales per dollar spent on total cost (phone rep plus web site) has increased each year during the six year period. This leads to the conclusion that the overall efficiency of sales is improving.

Part (b):Productivity (Sales/Web Site $) $95.80 $88.46 $81.18 $75.27 $68.48 $62.74 $78.66

year during the six year period.

ear.

there is a 1:1 relationship between costs (phone reps) may be nts elsewhere (e.g., web site). In this

ed each year during the six year oving.

Part (d): Productivity (Sales/Total $) $19.16 $20.91 $22.55 $24.35 $25.46 $26.79 $23.20

Les

Required Performance (Seconds) (Seconds) Efficiency 60 70 85.71%

Other performance measures that might be important include the number of errors (quality), other tasks Les may be able to complete in addition to this form, etc.

CUSTOMER ABC Company Preztel SCR Industries BeetleBob

ACTUAL TIME REQUIRED TO PERFORM ROUTINE MAINTENANCE (hours) 1.8 2.4 1.9 1.8

STANDARD TIME TO PERFORM ROUTINE MAINTENANCE (hours) EFFICIENCY 2.0 111.11% 2.0 83.33% 2.0 105.26% 2.0 111.11% AVERAGE: 102.70%

The rep's average efficiency is 102.70%. According to this measure of her performance, she exceeds the efficiency standard for performing routine maintenance.

a.) Standard Time Actual Time Taken to to Replace a Replace a Fender Fender (hours): (hours): 2.5 4.0

Efficiency 62.50%

Hourly Insurance Reimbursed $50

Standard Time to Replace a Fender (hours): 2.5

Total $ Reimbursed Labor $125

Hourly Labor Pay Rate: $35

Actual Time Taken to Replace a Fender (hours): 4.0

Total $ Costs Labor $140

No, Gibson's will not make money on the job. They will lose $15. b.) Total $ Reimbursed Labor $125

Hourly Labor Pay Rate: $35

Time Required to Break Even Replacing a Fender (hours): 3.57

Standard Time Time Required to Efficiency Required to to Replace a Break Even Replacing Break Even Replacing Fender (hours): a Fender (hours): a Fender: 2.5 3.57 70%

TIME TIME HAVING TIME HAVING PERCENT WAITING EYES PICTURE VALUEIN LINE TESTED TAKEN ADDED TIME 45 2 3 10.0% The key assumption here is that time spent waiting offers no value. In other words, if a person could enter the license bureau and immediately have his eyes checked and picture taken, he could be out the door in 5 minutes.

a.)

RIDE Magical Mushroom Haunted Roller Coaster

TOTAL PERCENT AVERAGE LENGTH PROCESS VALUEWAITING TIME OF RIDE TIME ADDED TIME 30 10 40 25.00% 40 5 45 11.11%

b.) TOTAL PERCENT AVERAGE LENGTH PROCESS VALUERIDE WAITING TIME OF RIDE TIME ADDED TIME Magical Mushroom 30 10 40 25.00% Haunted Roller Coaster 0 5 5 100.00% Total: 30 15 45 33.33%

Part a Process Step Dealer Emails Order Paper Order Created Order Sits in Inbox Internal Mail Delivers Order Order Sits in Clerk's Inbox Clerk Processes Order Worker Picks Order Inspector Checks Order Transport Firm Delivers Order Dealer Receives Order

Minutes

120 60 60 5 20 2 120

Total Process Minutes: Total Value-Added Minutes:

387 140

Percent Value-Added Time:

36.18%

Value-Added? no no no no no no yes no yes no

<--- NOTE: The percent value added will automatically update as the "yes" and "no" in cells C2:C11 are changed.

Answers can vary, depending on how the student interprets "value-added." For example, some students would argue that inspecting orders is necessary to assure correct orders. Others would argue that if the workers picked the order correctly, this wouldn't be necessary (hence, it's not value-added). Regardless, there is clearly a lot of non-value-added time in this process.

Part b

Dealer sends Order Electronically

In Stock?

YES

Worker Picks Order

Inspector Checks Order

NO Clerk notifies dealer and passes order on to plant Process Step Minutes Dealer sends Order Electronically

Value-Added? yes

Transport Firm Delivers Order

Dealer Receives Order

Worker Picks Order Inspector Checks Order Transport Firm Delivers Order Dealer Receives Order

20 2 120

Total Process Minutes: Total Value-Added Minutes:

142 140

Percent Value-Added Time:

98.59%

yes no yes yes

<--- NOTE: The percent value added will automatically update as the "yes" and "no" in cells C2:C11 are changed.

The impact on the number of lost orders would be tremendous, as the only known lost orders in the previous process occurred in the process before the order picking activity. Customer satisfaction would increase dramatically as the number of orders lost would be almost zero and the process cycle time is reduced to 142 minutes from 387 minutes.

Dealer Receives Order

1. It is not clear who or what organization is responsible for the entire process, and this is a key issue in many healthcare settings. One might argue that it is the general practitioner, but can he or she really monitor everything that is being done by specialists or hospital? Other s might argue that the patient is responsible, but the patient may be in even less of a position to do so. One solution has been the assignment of individual *case managers* to particularly complex healthcare processes. This might be someone with medical experience, such as an RN, whose primary job is to monitor each step of the process. Another approach is to house all activities within a single organization. For example, there might be a breast cancer clinic with its own dedicated staff and facilitiies. 2. In general, routine activities, such as scheduling appointments, ordering medical equipment, and forwarding medical records to required parties should be standardized to improve efficiency and eliminate mistakes. Variability is *not* good in these situations. Whether doctor's care itself should be artistic or standardized is a good question. For example, certain steps in radiology or surgery are almost certainly standardized. However, doctors and therapists need to be able to adjust to the unique requirements of a patient. For example, reconstructive surgery, follow-up medication regimens, etc. 3. Applying the Six Sigma process, I would first want to understand, via the "Define" stage, the scope of the problem and the potential costs, as well as potential benefits -- both monetary and non-monetary -- of improving the process. Ultimately, one could see certain process steps being streamlined and standardized, and information systems being put in place to make information available to all parties as required. More broadly, we might even reorganize the process. For example, why not have the patient meet *simultaneously* with the radiologist, oncologists and therapists?

key issue in many eally monitor nt is responsible, but

lex healthcare job is to monitor tion. For example,

ncy and eliminate

mple, certain steps s need to be able up medication

e, the scope of the -- of d and standardized, s required. More

Part a Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit: Cp =

1.4 kgs 1.4 kgs 0.15 kgs 1.7 kgs 1.1 kgs

0.6667

No, Tyler Apiaries is not capable of meeting the tolerance limits 99.7% of the time.

Part b Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit:

1.4 kgs 1.4 kgs 0.05 kgs 1.7 kgs 1.1 kgs

= (UTL - LTL) / 12

In order for Tyler Apiaries to achieve Six Sigma quality levels with regard to the weight of the bee packages, the company would need to reduce the standard deviation of package weight to .05 kgs.

Part c Average Bee Weight: Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit: Cp =

0.0001 kgs 1.4 kgs 1.4 kgs 0.1 kgs 1.7 kgs 1.1 kgs

which equals: which equals: which equals: which equals: which equals: which equals:

1 Bee 14000 Bees 14000 Bees 1000 Bees 17000 Bees 11000 Bees

1.0000

In order to control the process to meet the tolerance limits 99.7% of the time Tyler Apiaries will need to control the standard deviation to within 1000 bees. It may be easier to maintain control over the process by resetting their upper tolerance and lower tolerance limits using a measure of "number of bees" instead of the current method of weight.

Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit: Cpk=

1.4 kgs 1.5 kgs 0.2 kgs 1.7 kgs 1.1 kgs

0.3333

No, Tyler Apiaries is not capable of meeting the tolerance limits 99.7% of the time.

Leah's Toys - Rattles p: n:

0.01 200

Standard Deviation: Upper Control Limit (at 3 sigma): Lower Control Limit (at 3 sigma):

0.0070 0.0311 0.0000

Leah's Toys - Rubber Balls Part a Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit: Cp =

3 oz. 3 oz. 0.25 oz. 3.5 oz. 2.5 oz.

0.6667

No, Leah's Toys is not capable of meeting the tolerance limits 99.7% of the time. In order for the process to be in control Leah's Toys would need to reduce their standard deviation to approximately .166 oz., or change the tolerance limits to 3.75 and 2.25.

Part b Target Weight: 3 oz. Average Weight: 3 oz. Standard Deviation: 0.166667 oz. Upper Tolerance Limit: 3.5 oz. Lower Tolerance Limit: 2.5 oz. Cp =

= (UTL - LTL) / 6

1.0000

In order to exactly meet the tolerance limits 99.7% of the time, Leah's Toys would need to reduce the standard deviation to .16667 oz.

Part c Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit:

3 oz. 3 oz. 0.1 oz. 3.5 oz. 2.5 oz.

Standard deviation to meet six sigma levels:

0.083333 = (UTL - LTL) / 12

No, reducing the standard deviation to .1 oz. would not be enough for Leah's Toys to achieve Six Sigma quality levels with regard to the weight of the balls. However, it would be enough to exceed the 99.7% quality level (Cp > 1)

Leah's Toys - On Time Shipment SAMPLE 1 2 3 4 5

3 22 9 6 11

SAMPLE CUSTOMER ORDERS (HOURS TO SHIP) 5 21 4 15 9 7 3 16 8 16 11 38 11 25 2 5 17 2 19 4 2 7 18 9 16 18 7 10 10 20 18 1 6 3 18

6 15 4 1 9

Number Defective p 0 0 2 0.2222 0 0 0 0 0 0

a.) n: 9 p-bar: 0.0444 Standard Deviation: 0.0687 b.) In this situation using an absolute value instead of a continuous variable better represents the situation. The target is not an "average" time that is acceptable within upper and lower limits, but an absolute "pass" (less than or equal to 24 hours) or "fail" (greater than 24 hours).

Blue Bolt Part a Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit: Cp =

64 oz. 64 oz. 8 oz. 71 oz. 57 oz.

0.2917

Standard deviation to meet 99.7% quality levels =

2.333333 = (UTL - LTL) / 6

In order for the BlueBolt bottling process to meet the tolerance limits 99.7% of the time the standard deviation would need to be 2.3333 oz.

Part b Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit:

64 oz. 64 oz. 1.5 oz. 71 oz. 57 oz.

Standard deviation to meet 99.7% quality levels =

2.333333 = (UTL - LTL) / 6

The improved BlueBolt process is able to meet the tolerance limits more than 99.7% of the time (as 1.5 oz. is smaller than 2.33 oz.), but it is not capable of meeting Six Sigma quality levels. To achieve Six Sigma quality, the standard deviation would need to be reduced to 1.1666 oz.

River Rock Target Weight: x-2bar r-bar n: A2: D3: D4:

200 lbs. 200 lbs. 12 lbs. 12 0.27 0.28 1.72

UCLx: x-2bar: LCLx:

203.24 200 196.76

UCLr: r-bar: LCLr:

20.64 12 3.36

LaBoing p-bar: n: Standard Deviation:

0.07 100 0.0255

UCLp: p-bar: LCLp:

0.1465 0.0700 0.0000

AnderSet Laboratories Part a MEAN (MICRONS) (n = 4) 3.900 4.206 4.214 3.890 4.036 4.134 3.037 5.082 3.404 5.246 4.197 4.312 4.302 3.867 4.170

MINIMUM 3.617 3.971 4.062 3.749 3.501 3.543 2.935 3.797 2.837 5.106 4.085 3.949 3.989 3.617 4.046

MAXIMUM 3.989 4.302 4.400 3.937 4.084 4.584 3.929 5.695 4.255 6.382 4.239 4.356 4.400 3.900 4.206

X-bar 3.900 4.206 4.214 3.890 4.036 4.134 3.037 5.082 3.404 5.246 4.197 4.312 4.302 3.867 4.170

R 0.372 0.331 0.338 0.188 0.583 1.041 0.994 1.898 1.418 1.276 0.154 0.407 0.411 0.283 0.160

Part a x-2bar r-bar n: A2: D3: D4:

4.133 0.657 4 0.73 0 2.28

UCLx: x-2bar: LCLx:

4.613 4.133 3.654

UCLr: r-bar: LCLr:

1.498 0.657 0.000

Part b Yes, the process can be "under control" in statistical terms, but still fail to meet the needs of AnderSet's customers. The customers might have tolerance limits that are considerably tighter than the process is capable of delivering. Control charts will confirm that the process is stable, but will not confirm that the process is meeting customer needs.

Part c MEAN (MICRONS) (n = 4) 4.134 3.913 4.584 4.009 4.612 5.627

MINIMUM 4.011 3.891 4.499 3.934 4.085 5.183

MAXIMUM 4.612 4.474 5.145 4.891 4.983 6.080

X-bar 4.134 3.913 4.584 4.009 4.612 5.627

R 0.601 0.583 0.646 0.957 0.898 0.897

UCLx 4.617 4.617 4.617 4.617 4.617 4.617

X-2bar 4.137 4.137 4.137 4.137 4.137 4.137

6.000

X-Bar Chart

5.500 5.000

UCLx X-2bar

4.500

LCLx 4.000

X-bar

3.500 3.000 1

R Chart

2.900 2.400

1.900

UCLr r-bar

1.400

LCLr R

0.900 0.400 -0.100

3.9 4.206 4.214 3.89 4.036 4.134 3.037 5.082 3.404 5.246 4.197 4.312 4.302 3.867 4.17

3.617 3.971 4.062 3.749 3.501 3.543 2.935 3.797 2.837 5.106 4.085 3.949 3.989 3.617 4.046

3.989 4.302 4.4 3.937 4.084 4.584 3.929 5.695 4.255 6.382 4.239 4.356 4.4 3.9 4.206

LCLx 3.658 3.658 3.658 3.658 3.658 3.658

UCLr 1.498 1.498 1.498 1.498 1.498 1.498

r-bar 0.657 0.657 0.657 0.657 0.657 0.657

LCLr 0.000 0.000 0.000 0.000 0.000 0.000

Lazy B Ranch MEAN (SQ FEET) (n = 9) 13.2 12.8 13.3 13.1 12.7 12.9 13.2 13.0 13.1 12.7

MINIMUM 12.7 12.5 12.6 12.5 12.2 12.5 12.9 12.6 12.7 12.3

x-2bar r-bar n: A2: D3: D4:

13.000 0.880 9 0.34 0.18 1.82

UCLx: x-2bar: LCLx:

13.299 13.000 12.701

UCLr: r-bar: LCLr:

1.602 0.880 0.158

MAXIMUM 13.5 13.3 13.7 13.5 13.0 13.3 13.5 13.6 13.4 13.5

X-bar 13.200 12.800 13.300 13.100 12.700 12.900 13.200 13.000 13.100 12.700

R 0.800 0.800 1.100 1.000 0.800 0.800 0.600 1.000 0.700 1.200

It would be important for Lazy B Ranch to track this information because there is likely a minimum size requirement from their customers. It may be more difficult to reduce variability in the size of their product because their product is the result of live animals on their ranch. There may be some control offered by the equipment use to prepare the hides, but the size of the animals will affect the variability of the product.

Insurance Company p VALUES (n = 100) 0.08 0.11 0.12 0.06 0.13 0.09 0.16 0.09 0.18 0.15 Part a p-bar: n: Standard Deviation:

0.12 100 0.03

UCLp: p-bar: LCLp:

0.21 0.12 0.02

Part b p VALUES (n = 100) 0.90 0.12 0.25 0.10

UCLp 0.21 0.21 0.21 0.21

p-bar 0.12 0.12 0.12 0.12

LCLp 0.02 0.02 0.02 0.02

p VALUES

P chart 1.00 0.90 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10 0.00 1

Sample Number p

UCLp

p-bar

LCLp

Yes, it is statistically possible that a sample result could fall outside of the control limits due to pure chance. In fact, this should happen .3% of the time, since we set up the control chart to contain 99.7% of the samples. However, any sample outside the control limits should be investigated, as it is most likely a problem in the process. Part c p-bar: n: Standard Deviation:

0.12 50 0.05

UCLp: p-bar: LCLp:

0.25 0.12 0.00

The range between the upper control limit and lower control limit became wider when the sample size (n) was lowered from 100 to 50. This happens because the sample standard deviation increases as the sample size decreases.

EK Chemical Part a Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit: Cpk=

100 grams 100.5 grams 0.5 grams 102 grams 98 grams

1.0000

Yes, the process is capable of meeting the tolerance limits 99.7% of the time. Since the process capability index is exactly 1, there is not any room for error.

Part b Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit: Cp =

100 grams 100 grams 0.5 grams 102 grams 98 grams

1.3333

Yes, the process is capable of meeting the tolerance limits 99.7% of the time. In fact, since the process is now centered between the tolerance limits, there is more room for error than before.

Crawford Pharmaceuticals Target Amount: Average Amount: Standard Deviation:

100 mg 100 mg 0.25 mg

Part a Upper Tolerance Limit: Lower Tolerance Limit:

102 mg 98 mg

Part b Cp =

2.6667

Yes, the process is capable of meeting the tolerance limits 99.7% of the time. Because the process capability ratio is greater than 2, the process is capable of meeting Six Sigma quality levels as well. Part c Target Weight: 100 mg Average Weight: 100 mg Target Std. Deviation: 0.333333 mg Upper Tolerance Limit: 102 mg Lower Tolerance Limit: 98 mg Cp =

= (UTL - LTL) / 12

2.0000

In order to achieve exactly Six Sigma process capability levels, the standard deviation would need to be .3333 or 1/3. Because the current standard deviation is only .25 or 1/4 Crawford is already exceeding Six Sigma quality levels.

BHC Part a Target Weight: Average Weight: Standard Deviation: Upper Tolerance Limit: Lower Tolerance Limit: Cpk=

100 pounds 101 pounds 0.65 pounds 104 pounds 96 pounds

1.5385

We should use the process capability index in this situation, rather than the process capability ratio, because the process mean is not centered on the target.

Part b BHC may want to keep it's process mean above the target value to increase customer satisfaction, by increasing the likelihood of a bag of cement being more than 100 lbs. In effect, by setting the process mean above the target mean, they are deciding to err on the side of too much rather than too little.

Central Airlines DAY 1 2 3 4 5 6 7 8 9 10

SAMPLE SIZE 30 30 30 30 30 30 30 30 30 30

NO. OF LATEARRIVING FLIGHTS 2 3 4 0 1 6 4 2 3 5

p VALUES (n = 30) 0.0667 0.1000 0.1333 0.0000 0.0333 0.2000 0.1333 0.0667 0.1000 0.1667

Part a p-bar:

0.10

n: Standard Deviation:

30 0.05

UCLp: p-bar: LCLp:

0.26 0.10 0.00

Part b

Part c Some difficulties may arise by using a single control chart across different seasons when "normal" operations change. Because of this, Central Airlines may want to create different control charts to use during each season of the year, or they may wish to use the season in which they have the best performance to measure other seasons against. They should not use an average across all seasons.

Oceanside Apparel Company Part a x-2bar 36 inches r-bar 1.8 inches n: 4 A2: 0.73 D3: 0 D4: 2.28 UCLx: 37.314 x-2bar: 36.000 LCLx: 34.686 UCLr: r-bar: LCLr: Part b SAMPLE (n = 4) 1 2 3 4 5

4.104 1.800 0.000

MEASUREMENTS (IN INCHES) 37.3 36.5 38.2 36.2 33.4 35.8 37.9 36.2 32.1 34.8 39.1 35.3 36.1 37.2 36.7 34.2 32.1 34.0 35.6 36.1

MIN 36.2 33.4 32.1 34.2 32.1

MAX 38.2 37.9 39.1 37.2 36.1

X-bar 37.1 35.8 35.3 36.1 34.5

R 2.000 4.500 7.000 3.000 4.000

Inches

X-bar chart 38.00 37.50 37.00 36.50 36.00 35.50 35.00 34.50 34.00 33.50 33.00 1

Sample Number X-bar

UCLx

X-2bar

LCLx

R chart 8.00

7.00

Inches

6.00 5.00 4.00 3.00 2.00 1.00 0.00 1

Sample Number R

UCLr

r-bar

LCLr

UCLx 37.314 37.314 37.314 37.314 37.314

X-2bar 36.000 36.000 36.000 36.000 36.000

LCLx 34.686 34.686 34.686 34.686 34.686

UCLr 4.104 4.104 4.104 4.104 4.104

r-bar 1.800 1.800 1.800 1.800 1.800

LCLr 0.000 0.000 0.000 0.000 0.000

Calculating upper and lower control limits for a continuous variable (sample size = 5)

Sample 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

1 34.26 34.75 34.11 34.31 34.65 33.78 35.13 35.23 34.80 35.16 33.81 35.70 33.97 35.36 35.39

*** Observations *** 2 3 4 34.66 35.53 34.62 35.10 34.00 35.48 35.17 34.54 35.25 34.56 35.36 35.38 35.39 34.87 34.90 35.26 35.79 34.52 35.42 34.73 36.27 34.06 35.50 34.96 34.60 34.69 32.94 33.26 35.92 34.08 34.81 34.27 34.54 33.74 34.59 35.38 34.81 34.93 34.27 34.47 35.67 35.86 35.41 35.06 34.52

5 35.87 36.64 34.97 34.30 35.70 34.51 34.67 35.43 33.87 33.33 35.17 34.34 35.47 34.34 34.27 Average:

Upper control limit for sample means: Lower control limit for sample means:

35.78 33.88

Upper control limit for sample ranges: Lower control limit for sample ranges:

3.46 0.00

X-bar 34.99 35.19 34.81 34.78 35.10 34.77 35.24 35.04 34.18 34.35 34.52 34.75 34.69 35.14 34.93 34.83

R 1.61 2.64 1.14 1.08 1.05 2.01 1.60 1.44 1.86 2.66 1.36 1.96 1.50 1.52 1.14 1.64

Setting Up 99.7% Control Limits, Sampling by Attribute

Sample 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

No. of dissatisfied customers p-value 9 0.0900 11 0.1100 13 0.1300 8 0.0800 9 0.0900 10 0.1000 9 0.0900 8 0.0800 11 0.1100 12 0.1200 10 0.1000 7 0.0700 8 0.0800 9 0.0900 8 0.0800 8 0.0800 9 0.0900 10 0.1000 6 0.0600 9 0.0900 11 0.1100 8 0.0800 11 0.1100 6 0.0600 9 0.0900 9 0.0900 8 0.0800 12 0.1200 9 0.0900 11 0.1100

sample size = p-bar = st. dev =

100 0.0927 0.0290

UCL for sample p values: LCL for sample p values:

0.1797 0.0057

Question 1.) Dittenhoefer's competes on several dimensions of quality including features (protective coating, designs available), reliability (durability of china), conformance (designs not faded, all pieces match), aesthetics (look and design quality of china), serviceability (can the product be cleaned easily in the dishwasher), and perceived quality (how customers view the value of the product). These are being threatened by the manufacturing process creating defective product and the customer service department not being able to handle customer orders and issues. Question 2.) The current manufacturing process has two key problem areas. The first is the coating thickness of the polymer coating. The second is the temperature of the polymer coating during application. Process mapping and root cause analysis should be used to identify the failure points in the process, leading to elimination of process variability. Question 3.) PROBLEM

NUMBER

8 4

The key problems for customer support seem ot be the "Slow response to inquiries" and "Did not know status of customer's order". As the problem has been defined and measured, the DMAIC process could be used to resolve these issues by analyzing the root causes, improving the process, and controlling the process to ensure the improvements are maintained. Question 4.) Target Temperature Avg. Temperature Standard Deviation Upper Tolerance Lower Tolerance Cp =

0.6536

165 degrees 165 degrees 2.55 degrees 170 degrees 160 degrees

Target Thickness Average Thickness Standard Deviation Upper Tolerance Lower Tolerance Cp =

4 microns 4 microns 0.42 microns 5 microns 3 microns

0.7937

The polymer-coating process is not able to meet the engineering standards 99.7% of the time. The process capability index of both the temperature and the thickness are less than 1, meaning they are not capable.

Question 5.)

SAMPLE June 10 June 15 June 20 June 25

SAMPLE TEMPERATURE MEASUREMENTS (taken when the process was under control) OBSERVATIONS (degrees) X-bar 165 169 165 164 169 166.40 161 165 166 167 165 164.80 169 161 167 164 167 165.60 164 168 166 165 163 165.20

R 5 6 8 5

Order incorrect - wrong products shipped

Lost the order Order incorrect - wrong products shipped

Lost the order

Other problems, not listed above

Incorrect Pricing

Did not notify customer with regard to change in delivery date

Incorrect Pricing

90 80 70 60 50 40 30 20 10 0

Did not know status of customer's order

Slow response to inquiries

Slow response to inquiries Did not know status of customer's order Did not notify customer with regard to change in delivery date

June 30 July 05 July 10 July 15 July 20 July 25 July 30 August 05

166 168 162 163 167 167 163 163

x-2bar: r-bar: n: A2: D3: D4:

166 5.6 5 0.58 0 2.11

SAMPLE June 10 June 15 June 20 June 25 June 30 July 05 July 10 July 15 July 20 July 25 July 30 August 05

4.2 3.8 3.9 4.1 4.0 4.0 4.5 3.5 4.8 3.2 4.0 3.8

x-2bar: r-bar: n: A2: D3: D4:

4 0.9 5 0.58 0 2.11

168 163 164 168 167 163 165 165

169 167 169 165 164 168 165 169

163 164 167 165 167 165 169 165

166 166 163 167 164 168 163 163

166.40 165.60 165.00 165.60 165.80 166.20 165.00 165.00

6 5 7 5 3 5 6 6

SAMPLE TEMPERATURE MEASUREMENTS (taken when the process was under control) OBSERVATIONS (microns) X-bar 3.9 4.0 4.0 3.9 4.00 4.2 4.0 4.8 4.2 4.20 3.8 4.8 4.0 4.8 4.26 4.0 4.0 4.0 3.5 3.92 4.0 3.9 4.3 3.7 3.98 3.5 4.8 4.0 4.0 4.06 4.1 3.9 4.8 3.9 4.24 4.0 4.0 4.0 4.8 4.06 3.2 4.1 4.8 4.1 4.20 3.5 4.0 3.8 4.0 3.70 3.8 4.2 3.9 4.0 3.98 4.2 3.8 4.2 3.5 3.90

R 0.3 1 1 0.6 0.6 1.3 0.9 1.3 1.6 0.8 0.4 0.7

UCLx: 168.788 x-2bar: 165.550 LCLx: 162.312 UCLr: r-bar: LCLr:

11.781 5.583 0.000

UCLx: x-2bar: LCLx:

4.549 4.042 3.534

UCLr: r-bar: LCLr:

1.846 0.875 0.000

Fixed Cost: Variable Cost: Number of Copies 5000 10000

Total Cost $1,200 $1,700

$700 $0.10 Per Copy Cost $0.24 $0.17

Per Copy

Option 1 Option 2 a.) Demand Scenario: Option 1 Option 2 Demand Scenario: Option 1 Option 2

FIXED COST (PER YEAR) $500,000 $100,000

VARIABLE COST (PER UNIT) $2 $10

25,000 Total Cost $550,000 $350,000

Cost Per Unit $22 $14

75,000 Total Cost $650,000 $850,000

Cost Per Unit $9 $11

b.) As volume levels increase, Option 1 will be better, since the variable cost is lower. As volumes decrease, Option 2 will be better, as the fixed cost is lower.

c.) Indifference Point:

50,000

Units

Fixed Cost: Variable Cost: Number of Copies 5000 10000

Total Cost $1,200 $1,700

$700 $0.10

Per Copy

Per Copy Expected Cost Probability Cost $0.24 50% $600 $0.17 50% $850 Total: $1,450

Option 1 Option 2 a.) Demand Scenario: Option 1 Option 2 Demand Scenario: Option 1 Option 2 Demand Scenario: Option 1 Option 2

FIXED COST (PER YEAR) $500,000 $100,000

VARIABLE COST (PER UNIT) $2 $10

25,000 Total Cost $550,000 $350,000

Probability: Cost Per Unit $22 $14

30% Expected Cost: $165,000 $105,000

60,000 Total Cost $620,000 $700,000

Probability: Cost Per Unit $10 $12

40% Expected Cost: $248,000 $280,000

100,000 Total Cost $700,000 $1,100,000

Probability: Cost Per Unit $7 $11

30% Expected Cost: $210,000 $330,000

Option 1 Option 2

$623,000 $715,000

Total Expected Cost:

Based on the information given, I would select Option 1, as it has a lower expected cost.

b.) Demand Scenario: Option 1 Option 2 Demand Scenario: Option 1 Option 2 Demand Scenario: Option 1 Option 2

40,000 Total Cost $580,000 $500,000

Probability: Cost Per Unit $15 $13

30% Expected Cost: $174,000 $150,000

60,000 Total Cost $620,000 $700,000

Probability: Cost Per Unit $10 $12

40% Expected Cost: $248,000 $280,000

110,000 Total Cost $720,000 $1,200,000

Probability: Cost Per Unit $7 $11

30% Expected Cost: $216,000 $360,000

Option 1 Option 2

$638,000 $790,000

Total Expected Cost:

As the forecast shifted higher, Option 1 continues to be a better choice.

c.)

Forecast Probability

25,000

Option 1

30%

Forecast Probability 60,000 40%

Demand Outcome EC= $0

Forecast Probability 100,000 30%

Capacity Option Decision Forecast Probability 25,000 30% Option 2

Forecast Probability 60,000 40%

Demand Outcome EC= $0

d.) I would prefer Option 1, as the expected cost is lower.

Forecast Probability 100,000 30%

Expected Cost

$0 Expected Cost $0 Expected Cost $0

Expected Cost $0 Expected Cost $0 Expected Cost $0

a.) Revenue Per Unit:

In-House Contract b.) Indifference Point: c.) Demand Scenario: In-House Contract

$2,500 FIXED COST (PER YEAR) $55,000 $0

212

3,000 Total Cost $1,915,000 $2,640,000

VARIABLE COST (PER UNIT) $620 $880

Break-Even Volume Point 30 0

Units

Cost Per Unit $638 $880

From a cost perspective, I would prefer to assemble the stoves in-house as the cost per unit and total cost is less. This will be true for any forecasted demand above the indifference point of 212 units.

a.)

Take It

Accept the Current Offer or Wait?

Wait for It

Probability 100%

Salary $35,000

Probability 75%

Salary $45,000

Demand Outcome EV= $35,000

Demand Outcome EV= $33,750

b.) The key decision facing Emily is whether to take the definite $35,000 or the 75% chance of $45,000. The expected value of the $35,000 job is $35,000, while the expected value of the $45,000 job is only $33,750. c.) Other factors that Emily might consider, besides expected value, are the other opportunities that may be available besides the two jobs she is considering now, not to mention her personal preferences. She might want to wait on both jobs until she finds a position paying $55,000 per year so she can move out of her parents' basement

a.) Revenue Per Unit:

$25

Fireworks Sales

FIXED COST (PER YEAR) $12,000

b.) Revenue Per Unit:

$25

Original Expanded c.) Indifference Point:

FIXED COST (PER YEAR) $12,000 $20,000

2,667

VARIABLE COST (PER UNIT) $8

Break-Even Volume Point 706

VARIABLE COST (PER UNIT) $8 $5

Break-Even Volume Point 706 1,000

Units

a.) Revenue Per Patient:

$140 FIXED COST (PER YEAR) $70,000,000

VARIABLE COST (PER PATIENT) $80

Break-Even Volume Point 1,166,667

b.) Demand Scenario 1,000,000 2,000,000

Fixed Cost $70,000,000 $70,000,000

Variable Cost $80,000,000 $160,000,000

Revenue $140,000,000 $280,000,000

Profit -$10,000,000 $50,000,000

c.) Demand Scenario 1,000,000 2,000,000

Fixed Cost $70,000,000 $70,000,000

Variable Cost $80,000,000 $160,000,000

Revenue $140,000,000 $280,000,000

Profit -$10,000,000 $50,000,000

Laffolin Production

Probability 30% 70%

Total Expected Value: d.) Demand Level 1,000,000

Probability 30%

Profit -$10,000,000

Demand Level 2,000,000

Probability 70%

Profit $50,000,000

Demand Outcome

Yes

EV = $32,000,000 Make Laffolin? EV = $0 No

Profit $0 Demand Outcome

Expected Value -$3,000,000 $35,000,000 $32,000,000

Long-Run Averages: Arrival Rate: 20 Service Rate: 30

customers per hour customers per hour

a.) Utilization: 66.667% b.) Number Waiting: Number in System:

1.333 2

customers customers

0.067 0.1

hours hours

c.) Wait Time: Time in System:

a.) Long-Run Averages: Arrival Rate: 10 Service Rate: 15

calls per hour calls per hour

Number Waiting: Wait Time:

calls hours

1.333 0.133

b.) Long-Run Averages: Arrival Rate: 13 Service Rate: 15

calls per hour calls per hour

Number Waiting: Wait Time:

calls hours

5.633 0.433

As the arrival rate increases, the average number of calls waiting and the average wait time increase dramatically. From a customer service perspective, the busy Monday morning arrival times would not be sustainable long-term.

First Practice: Second Practice:

30 seconds 25.5 seconds

a.) Estimated Learning Curve:

85%

b.) Attempts Until 50% of First Run:

(from Table 6.4)

c.) No, it is not realistic to expect indefinite learning improvements because there are other limitations on the time it takes to complete the task besides the knowledge of the pit crew (such as the tools used and physical limits of the crew members themselves).

First Attempt: Second Attempt:

240 seconds 180 seconds

a.) Estimated Learning Curve: b.) Attempts Until 50% of First Run:

75%

c.) Time to Complete 20th Rescue: 91.44 (0.381 value taken from Table 6.4)

(from Table 6.4)

seconds

NOTE: Enter Inputs in Yellow-Shaded Cells. Revenue per unit of output:

Capacity Option 10 Servers 20 Servers 30 Servers Demand Scenario 15 Million 30 Million 45 Million

10 Servers 20 Servers 30 Servers

$0.50

Variable Cost Per Unit of Fixed Cost Output Max. Output $50,000 $0.005 20,000,000 $90,000 $0.003 40,000,000 $120,000 $0.002 60,000,000

Demand Level 15,000,000 30,000,000 45,000,000 Total:

Probability 30% 60% 10% 100%

*** Break-Even and Indifference Points *** Break-Even Point 10 Servers 20 Servers 101,011 ----181,087 20,000,000 --240,964 23,333,333 30,000,000

30 Servers -------

*** Results for Different Capacity/Demand Combinations *** Expected 15 Million 30 Million 45 Million Value 10 Servers $7,375,000 $9,850,000 $9,850,000 $9,107,500 20 Servers $7,365,000 $14,820,000 $19,790,000 $13,080,500 30 Servers $7,350,000 $14,820,000 $22,290,000 $13,326,000 a.) Break-Even 101011 hits 181087 hits 240964 hits

10 Servers 20 Servers 30 Servers

b.) Indifference Point between 10 and 20 servers:

20,000,000 hits

c.) 15 Million $7,375,000 $7,365,000 $7,350,000

10 Servers 20 Servers 30 Servers

30 Million $9,850,000 $14,820,000 $14,820,000

45 Million Expected Value $9,850,000 $9,107,500 $19,790,000 $13,080,500 $22,290,000 $13,326,000

The option for 30 servers will maximize expected value.

First Job: Second Job:

5 weeks 4 weeks

d.) Estimated Learning Curve: Time to complete her 6th Job:

80% 2.81

weeks

(using Table 6.4)

Time to finish next 5 jobs (3-7):

15.17

weeks

(using Table 6.4)

e.)

Long-Run Averages: Arrival Rate: Service Rate:

11 15

calls per hour calls per hour

Being Served:

0.733

calls

g.) Number Waiting:

2.017

calls

0.183 11.000

hours minutes

f.)

h.) Wait Time: Wait Time:

No, this is not an acceptable wait time given that it exceeds the 2.5 minutes stated in the policy.

NOTE: Enter Inputs in Yellow-Shaded Cells. *** Per Job Estimates *** Revenue:

$2,000.00

Cost: Labor Equipment

Hours 30 20

Per Hour $10.00 $20.00 Total Cost:

Total $300.00 $400.00 $700.00

*** Demand Scenario Estimates *** Demand Scenario High Medium Low

Part a)

Capacity Option High Capacity Med. Capacity Low Capacity

Demand Level 300 200 120 Total:

Probability 30% 40% 30% 100%

*** Capacity Option Estimates *** Number of Number of Equipment Break-Even Labor Hours Hours Fixed Cost Point $210,000 9,000 6,000 105 $157,500 6,750 4,500 79 $105,000 4,500 3,000 53

Max. Number of Jobs Handled 300 225 150

Part b) NOTE: Enter Inputs in Yellow-Shaded Cells. *** Per Job Estimates *** Revenue:

$2,000.00

Cost: Labor Equipment

Hours 30 20

Per Hour $10.00 $20.00 Total Cost:

Total $300.00 $400.00 $700.00

*** Demand Scenario Estimates *** Demand Scenario Demand Level Probability High Demand 300 30% Med. Demand 200 40% Low Demand 120 30% Total: 100% *** Capacity Option Estimates ***

Capacity Option

Number of Labor Hours

Number of Equipment Hours

Fixed Cost

Break-Even Point

High Capacity Med. Capacity Low Capacity

9,000 6,750 4,500

6,000 4,500 3,000

$210,000 $157,500 $105,000

105 79 53

*** Results for Different Capacity/Demand Combinations *** Expected High Demand Med. Demand Low Demand Profit High Capacity $204,000 $204,000 $204,000 $204,000 Med. Capacity $153,500 $153,500 $153,500 $153,500 Low Capacity $103,000 $103,000 $103,000 $103,000 High EP = $204,000 Demand Outcome

Capacity Option Decision

Medium EP = $153,500

Low EP = $103,000

Demand Outcome

Demand Level 300

Probability 30%

Demand Level 200

Probability 40%

Demand Level 120

Probability 30%

Demand Level 300 (225 is Max)

Probability 30%

Demand Level 200

Probability 40%

Demand Level 120

Probability 30%

Demand Level 300 (150 is Max)

Probability 30%

Demand Level 200 (150 is Max)

Probability 40%

Demand Level 120

Probability 30%

Max. Number of Jobs Handled

300 225 150

nations ***

Profit $204,000 Profit $204,000 Profit $204,000

Profit $153,500 Profit $153,500 Profit $153,500

Profit $103,000 Profit $103,000 Profit $103,000

NOTE: Enter Inputs in Yellow-Shaded Cells. Revenue per unit of output:

Capacity Option Option A Option B Option C Demand Scenario Low Medium High

Option A Option B Option C

$100.00

Variable Cost Per Unit of Fixed Cost Output Max. Output $0.00 $30.00 200 $1,250.00 $15.00 300 $4,000.00 $7.50 400

Demand Level 125 275 425 Total:

Probability 25% 55% 20% 100%

*** Break-Even and Indifference Points *** Break-Even Point Option A Option B 0.00 ----14.71 83.33 --43.24 177.78 366.67

Option C -------

*** Results for Different Capacity/Demand Combinations *** Expected Low Medium High Value Option A $8,750.00 $14,000.00 $14,000.00 $12,687.50 Option B $9,375.00 $22,125.00 $24,250.00 $19,362.50 Option C $7,562.50 $21,437.50 $33,000.00 $20,281.25

Average thoughput time for all laptops = I / T = (Total inventory) / (Total throughput) = 37/200 = 0.185 day

The average throughput time for a computer that goes through both refurbishing and testing = time in testing + Time in Refurbishing = 21/200 + 16/140 = 0.219 days Lenovo is meeting its performance goal of less than a day for laptops that are being both tested and refurbished.

Test

Refurbish

reject

Test

Refurbish

reject

hput) = 37/200 = 0.185 days

esting

Large Orders T = 2 days 20%

Order Assessment T = 0.25 days

50%

Small Orders T =0.5 days

Declined

Inventory in "order assessment" = R*T = 20*0.25 = 5 Inventory in "large orders" = 4*2 = 8 Inventory in "small orders" = 10*0.5 = 5 Total inventory = 18 orders Average time in the system = T = I/R = 18/20 = 0.9 days

NOTE: Enter Inputs in Yellow-Shaded Cells. Revenue per unit of output (first 14,400 lbs): Revenue per unit of output (after 14,400 lbs):

$7.00 $2.90

Variable Cost Per Unit of Fixed Cost Output $0.00 $3.00 $35,000.00 $1.60

Max. Output 14,400 40,000

Capacity Option No Roaster Buy Roaster Demand Scenario Low Medium High

No Roaster Buy Roaster

Demand Level (pounds) 18,000 25,000 35,000 Total:

Probability 33% 33% 33% 100%

*** Break-Even and Indifference Points *** Break-Even Indifference Point Point 0 --6,482 25,000

*** Results for Different Capacity/Demand Combinations *** Expected Low Medium High Value No Roaster $57,600.00 $57,600.00 $57,600.00 $57,600.00 Buy Roaster $47,440.00 $56,540.00 $69,540.00 $57,840.00 Question 1.) The two capacity options that Robbie needs to consider are buying vs. not buying a coffee roaster. The costs of not buying a roaster are $0.00 (Fixed) and $3.00 (Variable) while the costs of buying a roaster are $35,000 (Fixed) and $1.60 (Variable). The indifference point for the two options is 25,000 pounds of coffee. Since the indifference point is higher than the 14,400 that Robbie will use internally, the implication is that he will need to sell coffee externally if he buys the roaster.

Yes

Demand Outcome

EV = $57,840

Demand Level 18,000

Probability 33%

Profit $47,440

Demand Level 25,000

Probability 33%

Expected Value $56,540

Demand Level 35,000

Probability 33%

Profit $69,540

Demand Level 25,000

Probability 100%

Profit $57,600

Buy Roaster?

Demand Outcome

EV = $57,600 Question 2.) The demand scenarios do not make a difference in the expected profit if Forster's does not invest in the roaster since all of the demand scenarios are greater than the 14,400 maximum that Forster's will sell in-house. Question 3.) The decision tree reflects the total expected values for each of the two capacity options. Question 4.) The worst possible financial outcome for Forster's is that they decide to invest in the roaster and the demand is low. The best possible financial outcome is if they invest in the roaster and the demand is high. Other factors that Robbie should consider are that the difference between the expected value of buying vs. not buying the roaster are only $240 for the year and buying a roaster ties up $35,000 of capital. Also, if selling coffee is the core competency of the company, then roasting coffee would be a significant strategic realignment.

Queuing model formulas for a simple single line, single server queuing sy with random arrivals and service times (M/M/1) (Make changes to yellow cells only)

What are the "units" being served? What are the time periods? (hours, days, etc.) What is the arrival rate per time period? What is the service rate per time period?

Planes Hours 8.5 12

Part a) Ave. # waiting (Lq) Ave. # in system (Ls)

1.72 Planes 2.43 Planes

Part b) Ave. time waiting (Wq): Ave. time in system (Ws):

0.20 Hours 0.29 Hours

Planes Planes

Queuing model formulas for a simple single line, multiple server queuing s with random arrivals and service times (M/M/C) (Make changes to yellow cells only) Arrival rate (l) Service rate (m)

15 planes per hour 12 planes per runway, per hour

IMPORTANT: The formulas are only valid if the cumulative service rate exceeds the arrival rate (c*m > l)

Number of servers (c) 1 2

Probability of zero planes in the system (P0) --23.08%

Average Average number number Average of planes of planes time in Average in system in line system time in (Ls) (Lq) (Ws) line (Wq) --------2.051 0.801 0.14 0.05

Part c) The results for the single line, multiple server model show that with two runways, the average number of planes waiting will be 0

Part d) The results for the single line, multiple server model show that with two runways, the average time waiting will be 0.05 hours, or

le server queuing system

iple server queuing system

number of planes waiting will be 0.801

time waiting will be 0.05 hours, or about 3 minutes.

Queuing model formulas for a simple single line, single server queuing sy with random arrivals and service times (M/M/1) (Make changes to yellow cells only)

What are the "units" being served? What are the time periods? (hours, days, etc.) What is the arrival rate per time period? What is the service rate per time period?

Customers hours 11 Customers 15 Customers

Part a) Ave. # waiting (Lq) Ave. # in system (Ls)

2.02 Customers 2.75 Customers

Part b) Ave. time waiting (Wq): Ave. time in system (Ws):

0.18 hours 0.25 hours

Customers have to wait on average 0.18 hours to be checked out. This translates into 0.18*60 = 10.8 minutes. This number seems a little high. However, before Hector's decides on whether they want a second checkout register, they need to: 1. Consider the additional hourly costs of a checkout person and register. 2. Identify the impact on waiting times. 3. Assess how much additional profit they would incur by shortening the waiting times. 4. Determine whether the additional costs of staffing a second register are more than covered by the additional profit.

Queuing model formulas for a simple single line, multiple server queuing s with random arrivals and service times (M/M/C) (Make changes to yellow cells only) Arrival rate (l) Service rate (m)

11 customers per hour 15 customers per hour, per clerk

IMPORTANT: The formulas are only valid if the cumulative service rate exceeds the arrival rate (c*m > l)

Number of servers (c) 1 2

Probability of zero customers in the system (P0) 26.67% 46.34%

Average number of Average Average customers number of time in Average in system customers in system time in (Ls) line (Lq) (Ws) line (Wq) 2.750 2.017 0.25 0.18 0.847 0.114 0.08 0.01

Part c) The average number of customers in line with a second register is 0.114 customers (down from 2.017 for a single register). This number seems very reasonable. Part d) Time in line drops from 0.18 hours (roughly 11 minutes) to less than a minute. This is a signicant improvement, but the question remains ==> is it worth the cost?

Queuing model formulas for a simple single line, single server queuing sy with random arrivals and service times (M/M/1) (Make changes to yellow cells only)

What are the "units" being served? What are the time periods? (hours, days, etc.) What is the arrival rate per time period? What is the service rate per time period?

Parts hours 100 150

Part a) Ave. # waiting (Lq) Ave. # in system (Ls)

0.67 Parts 1.33 Parts

Part b) Ave. time waiting (Wq): Ave. time in system (Ws):

0.01 hours 0.01 hours

Parts Parts

le server queuing system

λ= 4

Arrivals 0 1 2 3 4 5 6 7 8 9 10

Time Period 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Probability n arrivals 0.0183 0.0733 0.1465 0.1954 0.1954 0.1563 0.1042 0.0595 0.0298 0.0132 0.0053

Cumulative probability 2% 9% 24% 43% 63% 79% 89% 95% 98% 99% 100%

Random no. 75.60 74.03 80.70 22.18 88.12 75.95 47.38 10.63 34.96 42.99 83.14 2.68 8.21 73.41 39.71 73.79 99.70 22.89 19.32 64.51 Average =

Simulated Arrivals 4 4 5 1 5 4 3 1 2 2 5 0 0 4 2 4 9 1 1 4 3.05

Assigned random numbers (0 to 100) Arrivals 0<r<2 0 2<r<9 1 9 < r < 24 2 24 < r < 43 3 43 < r < 63 4 63 < r < 79 5 79 < r < 89 6 89 < r < 95 7 95 < r < 98 8 98 < r < 99 9 99 or greater 10

Crew 1 Cars

Driveway Crew 2

Washed cars

For the SimQuick model, not only would we need to add an additional workstation called "Crew 2", but we would also need to make sure that "Crew 2" was listed as the possible output destinations for "Driveway"

EARNINGS AND EXPENSES (YEAR ENDING JANUARY 2019) Sales $50,000,000 New Cost of goods sold (COGS) $27,000,000 Old Pretax earnings $5,000,000 + 10% reduction in COGS $3,000,000 New pretax earnings $8,000,000 SELECTED BALANCE SHEET ITEMS New merchandise inventory $2,250,000 Old total assets $8,000,000 - 10% reduction in merchandise inv. $250,000 Net total assets $7,750,000 Part b) Profit margin 16% Return on assets (ROA) 103%

EARNINGS AND EXPENSES (YEAR ENDING JANUARY 2019) Sales $50,000,000 Cost of goods sold (COGS) $30,000,000 Pretax earnings $5,000,000 SELECTED BALANCE SHEET ITEMS Merchandise inventory $2,500,000 Total assets $8,000,000 Part c) With the current profit margin of 10%, Dulaney's would need to increase sales by $30,000,000 to have the same effect on pretax earnings as a 10% decrease in merchandise costs.

PERFORMANCE DIMENSION Price Quality Delivery Reliability Total:

IMPORTANCE 0.3 0.4 0.3 1 Scores:

POTENTIAL SOURCES AARDVARK BEVERLY HILLS CONAN THE ELECTRONICS INC. ELECTRICIAN 4 3 5 3 5 5 4 2 1 3.6

3.5

3.8

Based on the new results, Electra should change its supplier to Conan the Electrician, as it has the highest overall weighted score.

Total Cost Analysis for the Sourcing Decision at ABC INSOURCING OPTION Operating Expenses Direct Labor Benefits Direct Material Indirect Labor Benefits Equipment Depreciation Overhead Engineering / design costs Total cost per unit

$0.0300 $0.0150 $0.0500 $0.0110 $0.0055 $0.0100 $0.0300 $0.0300 $0.1815

OUTSOURCING OPTION 1 Purchase Price Shipping and handling Inventory Charges Administrative costs Total cost per unit

$0.1000 $0.0100 $0.0050 $0.0007 $0.1157

Savings per unit Total savings

$0.0658 $65,800

a.) OUTSOURCING -- New supplier Purchase Price Shipping and handling Inventory Charges Administrative costs Total cost per unit

$0.0800 $0.0150 $0.0070 $0.0009 $0.1029

Savings per unit Total savings

$0.0786 $78,600

50%

of Direct Labor

50% $10,000

of Indirect Labor absorbed over 1,000,000 units

$30,000

absorbed over

$20

per month, for

1,000,000 units

months, over 1,000,000 units

1,000,000 units

$25

per month, for

1,000,000 units

The outsourcing option with new supplier is the least expensive option of the three options (see Example 7.5).

b.) INSOURCING -- Volume increases to 1.5 million units Operating Expenses Direct Labor $0.0300 Benefits $0.0150 Direct Material $0.0500 Indirect Labor $0.0110 Benefits $0.0055 Equipment Depreciation $0.0067 Overhead $0.0300 Engineering / design costs $0.0200 Total cost per unit $0.1682

50%

50% $10,000 absorbed over

1,500,000 units

$30,000

1,500,000 units

absorbed over

The difference in cost per unit is explained by the larger volume absorbing the fixed "equipment depreciation" and "engineering / design costs".

c.) Other factors, besides cost, that should be considered by ABC when deciding whether or not to oursource the molded parts include whether the manufacture of parts is a core-competency of the firm as well as what quadrant of their strategic portfolio the part will occupy (Figure 7.1).

a.) GRANVILLE MAINTENANCE BUDGET - 2020 Assumptions:

INSOURCING OPTION Direct expenses (per worker) Wages Benefits Maintenance, repair, and operating supplies Indirect expenses Supervisory salary Benefits Other office expenses Total cost for year

4 1

workers supervisor

$120,000 $42,000 $96,000

$2,500 per worker, per month 35% of wages, per worker, per month $2,000 per worker, per month

$36,000 $14,400 $6,000 $314,400

$3,000 per supervisor, per month 40% of wages, per supervisor, per month $500 per month

OUTSOURCING OPTION Maintenance contract Total cost for year

$300,000 $300,000

Total Savings

$14,400

b.) Besides cost, Granville may also want to consider the quality of the maintenance provided and the schools' responsibility to support its community, which may mean keeping the current employees even though the cost is marginally higher. Another option may be to reduce one of the employees to parttime status or to lay-off one of the employees in order to reduce expenses to below that of the outsource option.

a.) PERFORMANCE DIMENSION Reputation Skill level Price Total:

POTENTIAL SOURCES IMPORTANCE 0.2 0.4 0.4 1 Scores:

ALTREX 3 5 5

TGI LTD. 4 4 3

PC ASSOCIATES 5 4 2

4.6

3.6

3.4

If the weights were changed so that each dimension had a weight of 1/3, Altrex would still be ranked highest, however TGI LTD. and PC Associates would be tied. b.) To incorporate the concept of order qualifiers into the weighted-point evaluation system, you could either eliminate them from contention before calculating weighted scores, or you could eliminate any supplier who scored less than a certain number in specific categories.

a.) PERFORMANCE DIMENSION Price Quality Delivery Total:

POTENTIAL SOURCES IMPORTANCE 0.2 0.2 0.6 1 Scores:

CARRIER A 3 4 4

CARRIER B 2 4 5

CARRIER C 5 2 2

3.8

4.2

2.6

Carrier B is best according to the weighted-point evaluation system.

b.) If the weights for price, quality, and delivery were changed to .6, .2, .2 respectively, carrier C would become the highest score in the weighted-point evaluation system, followed by carrier A and then carrier B.

c.) If Carrier B has the capacity to handle all of Flynn's business, then Flynn might consider singlesourcing with carrier B and try to work out a better price. On the other hand, a multiple or dual sourcing arrangement would provide Flynn with an alternative provider if Carrier B runs into difficulties.

Weighted-Point Evaluation System POTENTIAL SOURCES PERFORMANCE DIMENSION A B C D Total:

IMPORTANCE 0.20 0.30 0.30 0.20 1.00 Scores:

X1 1 2 2 4

X2 3 4 4 3

X3 2 3 3 2

X4 4 2 2 1

2.2

3.6

2.6

2.2

Question 1.) Total Cost Analysis for the Sourcing Decision at Pagoda Assumptions:

INSOURCING OPTION Personnel Cost: Wages Supervisory salary Equipment Cost: Servers PCs Variable Cost: Office supplies, fax paper, etc. Total cost for year

40 3 800,000

workers supervisor support contacts per year

$1,600,000 $210,000

$40,000 per worker $70,000 per supervisor

$8,000 $20,000

4 servers, at 20 PCs, at

$1,200,000 $3,038,000

$1.50 per request

OUTSOURCING (New Delhi) OPTION Fixed Cost: Administrative and IT Costs Variable Cost: Charge Total cost for year

$400,000.00 $1,900,000

Total Savings

$1,138,000

$2,000 $1,000

$1,500,000 $0.50 per request

The option to outsource the technical support center is cheaper by more than $1 million. Question 2.) Other factors to consider, besides cost, include the quality of support offered, the speed to answer requests, the percentage of downtime the vendor might experience due to connectivity issues, the amount of training the agents will require, and the cost of managing an offshore partner. I would weight the quality and speed of service highest, since these are the performance dimensions on which Pagoda competes. A weighted-point system could be used to compare the two options by assigning values to each dimension of the comparison and calculating the weighted scores.

Question 3.) I believe that Pagoda should not outsource its online help desk. As they are not competing in the lowcost area of the market, they should stay focused on their core-competencies of quality and communication with their customers. Outsourcing will remove them one step further from their customers, and result in the beginnings of a strategic shift from high-quality to low-cost. The risk of choosing a poor supplier and of losing control of their customer contacts are too great. Question 4.) Service measures that should be put in place include a quality metric of contacts resolved on first contact (not having to open a second contact for the same issue later), a time metric around the speed of answer for a customer opening a new support chat, and a customer satisfaction metric around how customers perceive the service received.

Service measures that should be put in place include a quality metric of contacts resolved on first contact (not having to open a second contact for the same issue later), a time metric around the speed of answer for a customer opening a new support chat, and a customer satisfaction metric around how customers perceive the service received.

per year per year

Bruin Logistics CUSTOMER Venetian Artists Supply Kaniko Ardent Furniture

SHIPMENT WEIGHT 100 boxes, drawing paper 3000 lbs. 100 PC printers 3000 lbs. 10 dining room sets 4000 lbs. Total: 10000 lbs.

OTHER COST INFORMATION Cost of direct shipment $2,000 per truck Maximum load: 20,000 lbs per truck Warehousing costs: $9 per hundred weight Delivery to final customer: $200 per customer CONSOLIDATED DELIVERY COSTS: Warehousing costs: $900 Cost of direct shipment: $2,000 Delivery to final customer: $600 Total: $3,500 a.) CUSTOMER Venetian Artists Supply Kaniko Ardent Furniture

SHIPMENT WEIGHT 100 boxes, drawing paper 3000 lbs. 100 PC printers 3000 lbs. 10 dining room sets 4000 lbs. Total: 10000 lbs.

OTHER COST INFORMATION Cost of direct shipment $2,000 per truck Maximum load: 20,000 lbs per truck Warehousing costs: $18 per hundred weight Delivery to final customer: $200 per customer CONSOLIDATED DELIVERY COSTS: Warehousing costs: $1,800 Cost of direct shipment: $2,000 Delivery to final customer: $600 Total: $4,400 b.) CUSTOMER Venetian Artists Supply Kaniko Ardent Furniture

SHIPMENT WEIGHT 100 boxes, drawing paper 3000 lbs. 100 PC printers 3000 lbs. 10 dining room sets 4000 lbs. Total: 10000 lbs.

OTHER COST INFORMATION Cost of direct shipment $2,000 per truck Maximum load: 20,000 lbs per truck

Warehousing costs: Delivery to final customer:

$9 per hundred weight $150 per customer

CONSOLIDATED DELIVERY COSTS: Warehousing costs: $900 Cost of direct shipment: $2,000 Delivery to final customer: $450 Total: $3,350 c.) CUSTOMER Venetian Artists Supply Kaniko Ardent Furniture

SHIPMENT WEIGHT 100 boxes, drawing paper 3000 lbs. 100 PC printers 3000 lbs. 10 dining room sets 4000 lbs. Total: 10000 lbs.

OTHER COST INFORMATION Cost of direct shipment $1,800 per truck Maximum load: 20,000 lbs per truck Warehousing costs: $9 per hundred weight Delivery to final customer: $250 per customer CONSOLIDATED DELIVERY COSTS: Warehousing costs: $900 Cost of direct shipment: $1,800 Delivery to final customer: $750 Total: $3,450

BosssMustang a.), b.) Consolidation versus Direct Truck Shipments No. of shipments Ave. shipment size: Truck capacity: Truck cost: Consolidation cost: Warehousing cost: Pickup cost:

10 500 lbs. 10,000 lbs. $800.00 per shipment $55.00 per hundred-weight $100.00 per supplier

SOLUTION No. of trucks needed: Warehousing costs: Pickup cost: Trucking costs: Total:

Consolidation 1 $2,750.00 $1,000.00 $800.00 $4,550.00

Single-order 10 $0.00 $0.00 $8,000.00 $8,000.00

The average truck utilization levels for the single-order shipment option would be 5%. The average truck utilization levels for the consolidation warehousing option would be 50%. c.) If trucking cost increases to $1200 it will change the consolidated shipping total to $4950 while changing the single-order shipment option total to $12,000. The consolidated option looks even better than it did before the change in trucking cost.

Astro Industries a.) Consolidation versus Direct Truck Shipments No. of shipments Ave. shipment size: Truck capacity: Truck cost: Consolidation cost: Warehousing cost: Delivery cost:

20 1,500 lbs. 40,000 lbs. $1,800.00 per shipment $75.00 per hundred-weight $100.00 per customer

SOLUTION No. of trucks needed: Warehousing costs: Delivery cost: Trucking costs: Total:

Break-bulk 1 $22,500.00 $2,000.00 $1,800.00 $26,300.00

Single-order 20 $0.00 $0.00 $36,000.00 $36,000.00

The average truck utilization levels for the single-order shipment option would be 3.75%. b.) By going with a break-bulk solution, Astro could save $9,700 per week. c.) The warehousing cost would need to be greater than $107.33 per hundredweight for the break-bulk option to be no more attractive than direct

Bartley Company a.) 5,400,000 million orders processed 25,000 delivered late 25,000 incomplete 25,000 damaged 20,000 billed incorrectly 85,000 Orders with at least one defect 98.43%

Percent perfect orders

b.) 5,400,000 million orders processed 25,000 delivered late 25,000 incomplete 25,000 damaged 20,000 billed incorrectly 90,000 Orders with at least one defect 98.33%

Percent perfect orders

c.) According to the logic of the perfect order measure, all failures of *any* part of the order process result in a failure of the order. This means that an incorrectly billed order has the same impact as a damaged order. This is reasonable as it is an absolute measure of the orders processed perfectly by the system. The implications are that an order with one error has the same weight as an order with several errors. The perfect order measure should be used in conjunction with other measures.

MountainMole Foods a.) YEAR 2015 Total 100,000 Shipments On-time 95,000 shipments Complete 99,000 shipments Undamaged 98,000 shipments Correctly billed 55,000 shipments # of Errors: 53,000 % Perfect: 47.00%

2016

2017

2018

150,000

175,000

190,000

145,000

170,000

180,000

142,500

157,500

161,500

147,500

173,000

189,000

97,500

132,000

161,500

67,500 55.00%

67,500 61.43%

68,000 64.21%

NOTE: These calculations assume that there is at most one error per order. The overall trend in performance is upward. The number of errors increases each year at a lower rate than the number of orders is increasing. b.) If I were looking to improve MountainMole's logistics performance, I would concentrate on the correct billing of shipments.

Northcutt a.)

Sets Needed:

1550

SUPPLIER A Acquisition Packing Freight Total Landed Cost:

PER UNIT $100.00 $2.00 $0.52 $102.52

PER MONTH $155,000.00 $3,100.00 $800.00 $158,900.00

SUPPLIER B Acquisition Packing International Shipping Freight Total Landed Cost:

PER UNIT $96.00 $3.50 $2.26 $0.52 $102.27

PER MONTH $148,800.00 $5,425.00 $3,500.00 $800.00 $158,525.00

SUPPLIER C Acquisition Packing International Shipping Freight Total Landed Cost:

PER UNIT $93.00 $3.00 $3.23 $0.65 $99.87

PER MONTH $144,150.00 $4,650.00 $5,000.00 $1,000.00 $154,800.00

775

3100

Supplier C is the cheapest. Supplier A is the most expensive. b.) Supplier A would have the lowest landed cost if the demand was cut in half (775 -- make the change above to see the results). Supplier C would have the lowest landed cost if demand was doubled to 3100. Supplier C has the highest fixed costs, and is therefore most sensitive to volume changes. c.) Other than price, Northcutt might consider the reliability of the supplier, the lead time and order quantities required by the vendors, the quality of the vendor, the reputation of the vendor, and the length of the contract terms offered by the vendor.

Redwing Automotive a.) PLS would need to reduce its per-unit price by $1.45 in order to match the SBC landed cost. This translates into almost a 5.2% price decrease. b.) As president of PLS, I might suggest that our on-time performance record would require less safety stock than they are currently considering. Also, there is the chance that with other US clients, PLS could take the warehousing costs and consolidate deliveries to multiple customers. c.) Logistics performance dimensions other than landed costs that may favor PLS could include on-time delivery, volume flexibility, and high percentage of perfect-order fulfillment.

CupAMoe's a.) Weighted Center of Gravity Model for up to Five Demand Points

Demand point Capital City Springfield Shelbyville

X coordinate 1.00 4.50 4.00

Y coordinate 5.00 3.00 1.00

Weighted X coordinate: Weighted Y coordinate:

Weighting factor 420000 250000 170000 2.65 3.60

b.) Weighted Center of Gravity Model for up to Five Demand Points

Demand point Capital City Springfield Shelbyville

X coordinate 1.00 4.50 4.00

Y coordinate 5.00 3.00 1.00

Weighted X coordinate: Weighted Y coordinate:

Weighting factor 800000 150000 150000 1.89 4.18

c.) I think that sales dollars is a better weighting factor as it will have a higher correlation to the amount of product shipped to an area than the general population number.

Green Valley a.) Weighted Center of Gravity Model for up to Five Demand Points

Demand point Birchwood Cactus Circle De La Urraca Kingston

X coordinate 5.00 7.00 2.00 3.50

Y coordinate 4.00 1.00 2.00 1.50

Weighted X coordinate: Weighted Y coordinate:

Weighting factor 163 45 205 30 3.71 2.60

b.) Other factors such as available space, zoning considerations, distance from other fire stations (to ensure coverage), may come into play when making the final decision for location.

Weighted Center of Gravity Model for up to Five Demand Points

Demand point A B C D E

X coordinate 1.00 2.00 3.00 4.00 5.00

Y coordinate 5.00 4.00 3.00 2.00 1.00

Weighted X coordinate: Weighted Y coordinate:

Weighting factor 300 200 100 300 300 3.08 2.92

The Assignment Problem: Flynn Boot Company Weekly Capacity Warehouse (Ci) Atlanta 20,000 Fort Worth 40,000 Tucson 30,000 TOTAL:

Weekly Demand Customer (Dj) BillyBob 27,800 DudeWear 8,000 Slickers 13,500 CJ's 33,000 TOTAL: 82,300

90,000

Cost to ship one pair of boots from Warehouse i to customer j (Tij)

Atlanta Fort Worth Tucson

BillyBob $2.00 $5.00 $1.00

DudeWear $3.00 $1.75 $2.50

Slickers $3.50 $2.25 $1.00

CJ's $1.50 $4.00 $3.00

Number of pairs of boots shipped from warehouse i to customer j

Atlanta Fort Worth Tucson TOTAL:

BillyBob 0 0 27800 27800

DudeWear 0 8000 0 8000

Slickers 0 11300 2200 13500

CJ's 20000 13000 0 33000

TOTAL: 20000 32300 30000

Objective Function: Minimum Total Shipping Costs: $151,425.00

a.) Minimize total shipping costs: $2.00*Sax + $2.00*Say + $3.50*Saz + $4.00*Sbx + $5.00*Sby + $4.50*Sbz + $3.00*Scx + $3.00*Scy + $3.00*Scz Subject to the following constraints: Total shipments from each warehouse must be less than its capacity: Sax + Say + Saz <= 400 Sbx + Sby + Sbz <= 500 Scx + Scy + Scz <= 100 Total shipments to each customer must at least cover demand: Sax + Sbx + Scx >= 200 Say + Sby + Scy >= 250 Saz + Sbz + Scz >= 300 All shipment quantities must be nonnegative: Sax, Say, Saz, Sbx, Sby, Sbz, Scx, Scy, Scz >= 0 b.) PLANT CAPACITY A 400 B 500 C 100 Total: 1000

STORE DEMAND X 200 Y 250 Z 300 Total: 750

PLANT A B C

X $2.00 $4.00 $3.00

Store Y $2.00 $5.00 $3.00

Z $3.50 $4.50 $3.00

PLANT A B C Total:

X 150 50 0 200

Store Y 250 0 0 250

Z 0 200 100 300

Total: 400 250 100

Objective Function: Minimum Total Shipping Costs: $2,200.00 Plant B appears to be underutilized as it is only shipping 250 units (1/2 of its capacity). This is the case because it is the most expensive plant to deliver units to any of the stores, perhaps it is too far away from the stores or requires special shipping. I would use this information to build expanded capability in either plant A or C but not at plant B.

Question 1.) In the recycling and refurbishing case the benefiting stakeholders are the original retailers of the products, the companies that are refurbishing the goods for profit, the consumers and people in general because there is less material in landfills. Many manufacturers have found that recycling and refurbishing are actually profitable, making them consistent with "good business practice" in the broadest sense.

Question 2.) Samsung would not have put the S.T.A.R. program in place if sustainability was not a focal point of the company, because with this program they stand to gain little to nothing in profits. They go beyond just recommending recycling by giving consumers locations and labels to help them make the right decision to recycle and this is an honorable effort that a non-sustainable company would not partake in. On the other hand, ATCLE’s refurbishing services is concerned with sustainability, but they are in the field because that are seeking a profit and only really focus on products that have 80% return of the original cost. Question 3.) I believe that sustainability will become a more prevalent concern for companies because it is important to many key stakeholders. Being sustainable affects the sourcing, purchasing and other functions of the supply chain all at one time.

Period 10 11 12 13 14 15

Demand Forecast 248 370 424 286 347 444 360 385

Period 10 11 12 13 14 15

Demand Forecast 248 370 424 333 286 408 444 327 397

Period 10 11 12 13 14 15

Demand Forecast 248 252.00 370 251.00 424 280.75 286 316.56 444 308.92 342.69

a = 0.25 1-a = 0.75

Month Jan-19 Feb-19 Mar-19 Apr-19 May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-19 Jan-20 Total:

Demand 119 72 113 82 82 131 111 116 89 95 88 90

Forecast

101 89 92 98 108 119 105 100 91 91

Forecast Error

Absolute Deviation

Absolute % Error

-19 -7 39 13 8 -30 -10 -12 -1

19 7 39 13 8 30 10 12 1

0.24 0.09 0.30 0.11 0.07 0.34 0.11 0.14 0.01

-20

139

1.39

MFE = -2 MAD = 15 MAPE = 0.15

Month Jan-19 Feb-19 Mar-19 Apr-19 May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-19 Jan-20 Total:

Demand 119 72 113 82 82 131 111 116 89 95 88 90

Forecast Forecast Absolute Absolute % Error Deviation Error

91 97 94 82 111 119 114 100 93 91 89

22 -15 -12 49 0 -3 -25 -5 -5 -1

22 15 12 49 0 3 25 5 5 1

0.20 0.18 0.15 0.37 0.00 0.03 0.28 0.05 0.05 0.01

137

1.32

MFE = 1 MAD = 14 MAPE = 0.13

Month Jan-19 Feb-19 Mar-19 Apr-19 May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-19 Jan-20 Total:

Demand

Forecast Forecast Absolute Absolute % Error Deviation Error 119 100 72 105.70 -33.70 33.70 0.47 113 95.59 17.41 17.41 0.15 82 100.81 -18.81 18.81 0.23 82 95.17 -13.17 13.17 0.16 131 91.22 39.78 39.78 0.30 111 103.15 7.85 7.85 0.07 116 105.51 10.49 10.49 0.09 89 108.65 -19.65 19.65 0.22 95 102.76 -7.76 7.76 0.08 88 100.43 -12.43 12.43 0.14 90 96.70 -6.70 6.70 0.07 94.69 -36.70 187.76 2.00

a = 0.3 1-a = 0.7 MFE = -3.34 MAD = 17.07 MAPE = 0.18

Period

Demand 1 2 3 4 5 6 7 8 9 10 11

Total:

221 247 228 233 240 152 163 155 167 158

Forecast

221 247 228 233 240 152 163 155 167 158

Forecast Error

Absolute Deviation

Absolute % Error

26 -19 5 7 -88 11 -8 12 -9

26 19 5 7 88 11 8 12 9

0.11 0.08 0.02 0.03 0.58 0.07 0.05 0.07 0.06

-63

185

1.07

MFE = -7 MAD = 21 MAPE = 0.12

ANSWER: This is not a good model because each month's forecast is based on only one observation. This makes it overly susceptible to randomness in the time series.

Period

Demand 1 2 3 4 5 6 7 8 9 10 11

Total:

221 247 228 233 240 152 163 155 167 158

Forecast Forecast Absolute Absolute % Error Deviation Error

233 235 235 203 178 157 162 160

0 5 -83 -40 -23 10 -4

0 5 83 40 23 10 4

0.00 0.02 0.54 0.25 0.15 0.06 0.02

-135

165

1.05

Weight on Period t-3: Weight on Period t-2: Weight on Period t-1: MFE = -19 MAD = 24 MAPE = 0.15

ANSWER: The forecast using this model is less accurate than the numbers from Problem 7. This occurred because of the sudden drop in demand starting in period 6. The 3-period weighted average takes longer to adjust to a sudden event than the last period model.

0.25 0.35 0.4

Period

Demand

First Forecast Absolute Forecast Error Deviation 221 250 247 244 3 3 228 245 -17 17 233 241 -8 8 240 240 0 0 152 240 -88 88 163 222 -59 59 155 210 -55 55 167 199 -32 32 158 193 -35 35 186 -292 298

1 2 3 4 5 6 7 8 9 10 11 Total: Period

First Forecast a = 0.2 1-a = 0.8 MFE = MAD =

Second Forecast a = 0.7 1-a = 0.3 MFE = -11 MAD = 19

Demand

Second Forecast Absolute Forecast Error Deviation 221 250 247 230 17 17 228 242 -14 14 233 232 1 1 240 233 7 7 152 238 -86 86 163 178 -15 15 155 167 -12 12 167 159 8 8 158 165 -7 7 160 -100 167

1 2 3 4 5 6 7 8 9 10 11 Total:

Plot of Demand vs. Forecasts 300 250 Demand

Units

200

First Forecast

150

Second Forecast

100 50 0 1

-32 33

Period

ANSWER: The Second Forecast model appears to work better because it more quickly adjusted to the period 6 drop in demand.

Month

Mar Apr May Jun Jul Aug Sep

Demand

220 2240 1790 4270 3530 4990

Forecast Forecast Adjusted Unadj. Trend a. b. Forecast Forecast Factor c. c. c.

1417 2767 3197 4263

2000 1895 3083 3306 4148

2354 3760 3847 4780

2000 1895 3083 3306 4148

700 459 677 541 631

Forecast b. a = 0.5 1-a = 0.5 Forcast c. a = 0.5 1-a = 0.5 b = 0.3 1-b = 0.7

Month Jan-15 Feb-15 Mar-15 Apr-15 May-15 Jun-15 Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15

Sales ($)

Unadjusted Trend Adjusted Table 9.12 Forecast Factor Forecast values $230,000 $220,000 $10,000 $230,000 $228,462 $230,000 $223,000 $5,800 $228,800 $233,287 $240,000 $225,100 $3,580 $228,680 $238,112 $250,000 $229,570 $4,114 $233,684 $242,937 $240,000 $235,699 $5,323 $241,022 $247,762 $250,000 $236,989 $2,903 $239,893 $252,587 $270,000 $240,893 $3,503 $244,396 $257,413 $260,000 $249,625 $6,641 $256,265 $262,238 $260,000 $252,737 $4,524 $257,261 $267,063 $260,000 $254,916 $3,117 $258,033 $271,888 $280,000 $256,441 $2,162 $258,603 $276,713 $290,000 $263,509 $5,105 $268,614 $281,538

a = 0.3 b = 0.6

ANSWER: The problem does not specify what the smoothing constants should be, so the instructor can either assign these or allow the students to choose values. The above answers for for alpha = 0.3 and beta = 0.6. Like the regression results shown in Table 9.12, the adjusted exponential smoothing model shows an upward trend in demand. Which one is best? We won't know until we have historical results to compare the two.

Month

Period Demand Unadjusted Trend Adjusted Forecast Factor Forecast Jan-18 1 1200 1100 60 Feb-18 2 1400 1125 46 1171 Mar-18 3 1450 1194 55 1249 Apr-18 4 1580 1258 59 1316 May-18 5 1796 1338 67 1406 Jun-18 6 2102 1453 86 1539 Jul-18 7 2152 1615 117 1732 Aug-18 8 2022 1749 124 1873 Sep-18 9 1888 1817 101 1919 Oct-18 10 1938 1835 68 1903 Nov-18 11 1988 1861 51 1912 Dec-18 12 1839 1893 43 1936 Jan-19 13 1684 1879 21 1900 Feb-19 14 1944 1830 -7 1823 Mar-19 15 1994 1859 7 1866 Apr-19 16 2154 1893 18 1910 May-19 17 2430 1958 37 1995 Jun-19 18 2827 2076 69 2145 Jul-19 19 2877 2264 117 2380 Aug-19 20 2687 2417 131 2548 Sep-19 21 2492 2485 106 2590 Oct-19 22 2542 2486 64 2551 Nov-19 23 2592 2500 44 2544 Dec-19 24 2382 2523 36 2559 Jan-20 25 2488 7 2495

a = 0.25 b = 0.4

This is 12

Month Period Jan-18 Feb-18 Mar-18 Apr-18 May-18 Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18 Dec-18 Jan-19 Feb-19 Mar-19 Apr-19 May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-19 Jan-20 Feb-20 Mar-20 Apr-20 May-20 Jun-20

Unadjusted Demand / Seasonal Adjusted Demand Forecast Forecast Index Forecast 1 1200 1457 82.3% 81.1% 1182 2 1400 1512 92.6% 91.2% 1379 3 1450 1566 92.6% 91.3% 1429 4 1580 1620 97.5% 96.2% 1558 5 1796 1675 107.3% 105.9% 1773 6 2102 1729 121.6% 120.2% 2078 7 2152 1783 120.7% 119.4% 2130 8 2022 1837 110.0% 109.0% 2003 9 1888 1892 99.8% 98.9% 1871 10 1938 1946 99.6% 98.7% 1921 11 1988 2000 99.4% 98.6% 1972 12 1839 2055 89.5% 88.8% 1824 13 1684 2109 79.9% 81.1% 1710 14 1944 2163 89.9% 91.2% 1974 15 1994 2217 89.9% 91.3% 2024 16 2154 2272 94.8% 96.2% 2185 17 2430 2326 104.5% 105.9% 2462 18 2827 2380 118.8% 120.2% 2861 19 2877 2435 118.2% 119.4% 2908 20 2687 2489 108.0% 109.0% 2713 21 2492 2543 98.0% 98.9% 2515 22 2542 2597 97.9% 98.7% 2564 23 2592 2652 97.7% 98.6% 2614 24 2382 2706 88.0% 88.8% 2402 25 2760 81.1% 2239 26 2815 91.2% 2568 27 2869 91.3% 2618 28 2923 96.2% 2811 29 2977 105.9% 3152 30 3032 120.2% 3643

SUMMARY OUTPUT Regression Statistics Multiple R 0.85 R Square 0.72 Adjusted R Square 0.71 Standard Error244.63 Observations 24.00 ANOVA df Regression Residual Total

Intercept Period

SS MS 1.00 3389243.27 3389243.27 22.00 1316538.06 59842.64 23.00 4705781.33

CoefficientsStandard Error 1403.07 103.07 54.29 7.21

t Stat 13.61 7.53

F Significance F 56.64 0.00

P-value Lower 95% Upper 95%Lower 95.0% Upper 95.0% 0.00 1189.31 1616.83 1189.31 1616.83 0.00 39.33 69.25 39.33 69.25

Comparing a Two-Period Moving Average and an Exponential Smoothing Model Two-period moving average model Weight on Period t-2: 0.35 Weight on Period t-1: 0.65

Period

Forecast Absolute Demand Forecast Error Deviation 1 60 2 53 3 65 55.45 9.55 9.55 4 72 60.80 11.20 11.20 5 72 69.55 2.45 2.45 6 74 72.00 2.00 2.00 7 50 73.30 -23.30 23.30 8 60 58.40 1.60 1.60 9 72 56.50 15.50 15.50 10 53 67.80 -14.80 14.80 11 56 59.65 -3.65 3.65 12 51 54.95 -3.95 3.95 13 51 52.75 -1.75 1.75 14 54 51.00 3.00 3.00 15 55 52.95 2.05 2.05 MFE = -0.008 MAD = 7.292

Exponential Smoothing Model Initial Forecast 65 Alpha (a): 0.3 Forecast Absolute Forecast Error Deviation 65.00 -5.00 5.00 63.50 -10.50 10.50 60.35 4.65 4.65 61.75 10.26 10.26 64.82 7.18 7.18 66.98 7.02 7.02 69.08 -19.08 19.08 63.36 -3.36 3.36 62.35 9.65 9.65 65.25 -12.25 12.25 61.57 -5.57 5.57 59.90 -8.90 8.90 57.23 -6.23 6.23 55.36 -1.36 1.36 54.95 0.05 0.05 MFE = -1.380 MAD = 7.350

Month Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 Jan-15 Feb-15 Jun-15 Jul-15 Total: Average:

Sales (Y) Temp (X) X^2 4670 5310 6320 7080 7210 7040 6590 5520 4640 4000 2840 3170

64390 5366

52 58 69 75 83 82 78 65 54 48 41 42 76 82 747 62

X*Y 2704 3364 4761 5625 6889 6724 6084 4225 2916 2304 1681 1764

b. Forecast

a = -767.7 b = 98.5

242840 307980 436080 531000 598430 577280 514020 358800 250560 192000 116440 133140 6718 7309

49041

4258570

ANSWER: a. Using the formula 9-8: 98.5 = =(E17-((C17*B17)/(COUNT(A3:A14))))/(D17((C17^2)/(COUNT(A3:A14)))) Using the formula 9-9: -767.7 = =B18-H2*C18 c. The regression model is a causal forecasting model because the number of golf balls forecast to be sold each month is dependent on the expected average temperature for the month.

Month 1 2 3 4 5 6 7 8 9 10 Total: Average: ANSWER: a. a= b=

Interest Rate (X)

Number of Loans (Y) 7% 20 5% 30 4% 35 8% 18 10% 15 6% 22 11% 15 9% 20 5% 27 12% 10 77% 212 8% 21.2

X^2

X*Y

0.0049 0.0025 0.0016 0.0064 0.01 0.0036 0.0121 0.0081 0.0025 0.0144 0.0661

1.4 1.5 1.4 1.44 1.5 1.32 1.65 1.8 1.35 1.2 14.56

41.1454 (intercept term) -259.0308 (regression coefficient for interest rate)

The regression model is a causal forecasting model because the number of loans forecast for each month is dependent on the expected interest rate for the month. (Answers will vary) b. The number of loans the bank should expect to make if the interest rate is 10%: 15.24229 , which rounds to 15 loans The number or loans the bank should expect to make if the interest rate is 6.5%: 24.30837 , which rounds to 24 loans Yes, these answers make sense as lower interest rates result in higher numbers of loans. (Answers will vary)

Demand = (35,000 + 4.8 * period) seasonal index Seasonal Indices Summer 1.25 Fall 0.90 Winter 0.75 Spring 0.90 ANSWER: a. True, the forecast of demand depends on the time period. b. True, as the time period increases so does the forecasted demand. c. True, the seasonal indices indicate that the demand in summer months (1.25) is higher than the demand during winter months (.75).

Quarter Winter Spring Summer Fall

Demand

Forecast Seasonal Index 285 250 1.14 315 300 1.05 300 350 0.86 400 400 1.00

ANSWER: The fall quarter season index is 1.00 so the unadjusted forecast will not be changed when multiplying by the seasonal index value (the other quarters will have a different unadjusted vs. seasonally adjusted forecast). As long as the seasonal index for fall equals 1, there is no need to multiply by the seasonal index.

Month

Cheese Balls

Jan-19 $126,500 Feb-19 $119,600 Mar-19 $115,200 Apr-19 $125,000 May-19 $112,800 Jun-19 $115,000 Jul-19 $126,900 Aug-19 $124,800 Sep-19 $135,200 Oct-19 $135,200 Nov-19 $151,200 Dec-19 $142,100 Total: $1,529,500 Percent: 50%

Cheese Nachos

Cheese Total Potato Sales Chips $69,000 $34,500 $230,000 $73,600 $36,800 $230,000 $81,600 $43,200 $240,000 $70,000 $55,000 $250,000 $64,800 $62,400 $240,000 $75,000 $60,000 $250,000 $75,600 $67,500 $270,000 $75,400 $59,800 $260,000 $83,200 $41,600 $260,000 $78,000 $46,800 $260,000 $72,800 $56,000 $280,000 $98,600 $49,300 $290,000 $917,600 $612,900 $3,060,000 30% 20%

Developing product type forecasts from aggregate forecasts in Figure 9.22 and percentages calculated above: Month

Cheese Balls

Cheese Nachos

Cheese Adjusted Potato Forecast Chips Jan-20 $143,135 $85,872 $57,357 $286,364 Feb-20 $145,547 $87,319 $58,323 $291,189 Mar-20 $147,959 $88,766 $59,290 $296,014 Apr-20 $150,370 $90,212 $60,256 $300,839 May-20 $152,782 $91,659 $61,223 $305,664 Jun-20 $170,713 $102,417 $68,408 $341,538 Jul-20 $198,584 $119,137 $79,576 $397,297 Aug-20 $218,424 $131,040 $87,527 $436,991 Sep-20 $238,771 $143,247 $95,680 $477,699 Oct-20 $230,778 $138,451 $92,477 $461,706 Nov-20 $234,154 $140,477 $93,830 $468,461 Dec-20 $237,531 $142,503 $95,183 $475,217 Total: $2,268,748 $1,361,100 $909,131 $4,538,979

Inches of Average Peak Acre-Feet of Rainfall Daily Temp, Water Used, Forecast Absolute Absolute % Year March-June July August Forecast Error Deviation Error 2005 12.5 78.4 39800 34598 5202 5202 0.13 2006 11.2 74.9 43700 33904 9796 9796 0.22 2007 12.2 84.1 45100 39967 5133 5133 0.11 2008 10.6 85.1 54500 43623 10877 10877 0.20 2009 9.3 70.6 32900 33583 -683 683 0.02 2010 11.7 71.0 31500 29714 1786 1786 0.06 2011 10.0 87.4 35500 46630 -11130 11130 0.31 2012 13.3 91.4 35800 44241 -8441 8441 0.24 2013 8.4 98.3 69700 58697 11003 11003 0.16 2014 14.9 99.6 48100 48403 -303 303 0.01 2015 10.0 91.7 53700 50283 3417 3417 0.06 2016 12.6 91.6 40300 45639 -5339 5339 0.13 2017 10.6 81.5 32600 40564 -7964 7964 0.24 2018 7.1 77.0 34100 42879 -8779 8779 0.26 2019 11.3 83.9 36800 41376 -4576 4576 0.12 Total: 0 94426 2.28

MFE = Tracking Signal = MAD = MAPE =

SUMMARY OUTPUT Regression Statistics Multiple R 0.7048242 R Square 0.4967771 Adjusted R Square 0.4129067 Standard Error 8109.7117 Observations 15 ANOVA df Regression Residual Total

2 12 14

SS MS F Significance F 779100240.8 389550120.4 5.923147 0.016239 789209092.5 65767424.37 1568309333

Coefficients Standard Error t Stat P-value Lower 95%Upper 95% Lower 95.0% Upper 95.0% Intercept -10095.398 21343.9989 -0.4729853 0.644711 -56600 36409.18 -56600 36409.18 Rainfall -1753.7134 1148.112468 -1.52747528 0.152562 -4255.24 747.8087 -4255.24 747.8087 Temperature849.68123 250.2383932 3.39548708 0.005314 304.4586 1394.904 304.4586 1394.904 ANSWER: The R^2 value for the model is .49, indicating that the model explains 49% of the variance in the dependent variable. The model appears to be good, since the tracking signal equals 0, meaning that the forecast is centered on the actual demand. Also, MAD is an average of only 15% off of actual demand.

0 0 6295 0.15

Period

Actual Forecast Forecast Absolute Absolute % Forecast Forecast Absolute Absolute % Demand Model 1 Error Deviation Error Model 2 Error Deviation Error 8 248 364 -116 116 0.47 486 -238 238 0.96 9 357 280 77 77 0.22 341 16 16 0.04 10 423 349 74 74 0.17 295 128 128 0.30 11 286 416 -130 130 0.45 364 -78 78 0.27 12 444 354 90 90 0.20 380 64 64 0.14 Total: -5 487 1.52 -108 524 1.72 ANSWER: Forecast Model 1 is best because it has a MFE closer to 0, meaning less bias, and a lower MAD and MAPE, meaning less total error.

Forecast Model 1: MFE = -1 MAD = 97 MAPE = 0.30 Forecast Model 2: MFE = -22 MAD = 105 MAPE = 0.57

Month January February March April May Jun Total:

Demand

Forecast Forecast Absolute Absolute % Error Deviation Error 1040 1055 -15 15 0.01 990 1052 -62 62 0.06 980 900 80 80 0.08 1060 1025 35 35 0.03 1080 1100 -20 20 0.02 1000 1050 -50 50 0.05 -32 262 0.26

MFE = -5 MAD = 44 MAPE = 0.04

ANSWER: The forecast model over-forecasts by an average of 5 units each month.

Total demand 2900 2700 2500 2300 Total demand

2100 1900 1700

SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations

1.00 1.00 1.00 7.03 24.00

ANOVA df Regression Residual Total

Intercept Period

SS 483513.03 1086.60 484599.63

MS 483513.03 49.39

Coefficients Standard Error 2105.32 2.96 20.50 0.21

t Stat 710.97 98.94

1.00 22.00 23.00

F Significance F 9789.53 0.00

P-value 0.00 0.00

Lower 95% 2099.17 20.07

Upper 95% Lower 95.0% Upper 95.0% 2111.46 2099.17 2111.46 20.93 20.07 20.93

ANSWER: 1. The linear regression model fits the sample data extremely well. The R^2 value for the model is .99, indicating that the model explains 99% of the variance in the dependent variable. Note that we forecasted total demand because it is this value that we are interested in when determining whether or not Top-Slice needs to expand capacity.

2. According to the model, Top Slice will need to have the expanded work cell up and running by August 2016. Because it will take at least 3 months to plan for and implement the expanded work cell, Jacob will need to start the expansion effort no later than May.

Jacob will need to ask about the certainty of the vice president's information and more detail about the effect the outcome will have on sales. The answers affect the forecast because they may indicate a change in the environment rendering the forecast model ineffective. Using quantitative forecasting under these circumstances makes sense only until reliable information indicates the environment is changing.

May-19

Feb-19

Oct-18

Jul-18

Apr-18

1500

Dec-17

1410 1417 1434 1452 1466 1483 1490 1505 1521 1536 1547 1554 1562 1574 1587 1595 1613 1631 1642 1656 1673 1685 1703 1720

Forecast, total Sir Slice-A-Lot Total demand demand 377 343 2130 2126 381 344 2142 2146 387 346 2167 2167 391 349 2192 2187 396 350 2212 2208 400 352 2235 2228 403 354 2247 2249 409 357 2271 2269 412 359 2292 2290 420 363 2319 2310 423 365 2335 2331 426 367 2347 2351 431 369 2362 2372 437 371 2382 2392 441 375 2403 2413 445 377 2417 2433 454 381 2448 2454 461 384 2476 2474 464 386 2492 2495 471 389 2516 2515 477 392 2542 2536 480 394 2559 2556 485 396 2584 2577 490 399 2609 2597 2618 2638 2659 2679 2700 2720 2741 2761 2782

Sep-17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

Hook King

Jun-17

Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 Nov-17 Dec-17 Jan-18 Feb-18 Mar-18 Apr-18 May-18 Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18 Dec-18 Jan-19 Feb-19 Mar-19 Apr-19 May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-19

Bomber

Mar-17

Period

Nov-16

Month

SERVICE SERVICE MIX LABOR HOURS PER JOB Light Cleaning 20% 0.2 Medium Cleaning 60% 0.25 Deep Cleaning 20% 0.35 Weighted Planning Value

a.) 0.04 0.15 0.07 0.26

b.) 10% 65% 25%

0.02 0.16 0.09 0.27

b.) The weighted planning value increased because a higher percentage of the service mix was in the more labor intense services.

GAUGE PRODUCT MACHINE HOURS LABOR HOURS a.) b.) SET MIX PER UNIT PER UNIT Machine Labor Mix Machine Labor A20 60% 0.20 0.15 0.12 0.09 45% 0.09 0.07 B30 15% 0.35 0.10 0.05 0.02 30% 0.11 0.03 C40 25% 0.25 0.12 0.06 0.03 25% 0.06 0.03 Weighted Planning Values 0.24 0.14 0.26 0.13 a.) The weighted planning values are the weighted average of the machine hours and labor hours required, based on the product mix.

b.) The weighted planning values changed because of the change to the product mix. The greater percentage of B30 results in more machine hours and less labor hours, on average.

PRODUCT MACHIN LABOR a.) b.) Model MIX E HOURS Machine Labor Mix Machine Labor Deluxe Models 45% 10.0 5.0 4.50 2.25 30% 3.00 1.50 Regular Models 30% 8.0 4.0 2.40 1.20 30% 2.40 1.20 Economy Models 25% 6.0 3.5 1.50 0.88 40% 2.40 1.40 Weighted Planning Values 8.40 4.33 7.80 4.10 a.) The assumptions that must be made in order to use the weighted perunit planning values for labor and machine time are that the averages of machine and labor hours are accurate (and there is a small standard deviation from the average) and that the product mix is accurate. c.) When the product mix changes from month to month, Bangor should use a bottom-up approach to sales and operations planning. Top-down approach should be used only when the product mix remains stable.

MONTH October November December January February March

SALES WORKE MACHIN WORKERS MACHINES FORECAST R E NEEDED NEEDED 44,000 39600 880 248 6 52,000 46800 1040 293 7 68,000 61200 1360 383 9 69,000 62100 1380 388 9 58,000 52200 1160 326 7 46,000 41400 920 259 6

Average Worker Hours Per Unit Average Machine Hours Per Unit Hours Available Per Month

0.9 0.02 160

MONTH January February March April May June

FORECAST FORECAST a.) COMBINED b.) TOTAL LABOR PRODUCT A PRODUCT B FORECAST HOURS REQUIRED 3500 700 4200 10010 3300 1000 4300 10050 3200 1200 4400 10160 3000 1500 4500 10200 2700 1900 4600 10170 2600 2100 4700 10280

Average Labor Per Product A Average Labor Per Product B

2.5 1.8

a.) If the combined forecast was the only information available, an increase in resource requirements from January to June would be expected.

b.) Although the total number of products forecasted increases from January to June, the product mix also changes. The result is that the total number of labor hours does not increase as much as would be expected if the only information available was the combined forecast.

c.) Bottom-up planning would be better suited for S&OP in this situation because the product mix changes from month to month. Top-down planning should be used when the product mix is stable.

MONTH March April May June July August September October November December January February Totals Costs Hiring: Layoff: Inventory: Cost of plan:

SALES IN WORKERS NEEDED FORECASTED WORKER TO MEET SALES ACTUAL ACTUAL SALES HOURS AVERAGE = 252 WORKERS PRODUCTION 227 1,592 31,840 199 252 2,016 1,400 28,000 175 252 2,016 1,200 24,000 150 252 2,016 1,000 20,000 125 252 2,016 1,504 30,080 188 252 2,016 1,992 39,840 249 252 2,016 2,504 50,080 313 252 2,016 2,504 50,080 313 252 2,016 3,000 60,000 375 252 2,016 3,000 60,000 375 252 2,016 2,504 50,080 313 252 2,016 1,992 39,840 249 252 2,016 227 24,192 24,192

$75,000 $50,000 $193,344 $318,344

LAYOFFS

HIRINGS

0 0 0 0 0 0 0 0 0 0 0 0 25 25

25 0 0 0 0 0 0 0 0 0 0 0 0 25

ENDING INVENTORY 1,000 1,424 2,040 2,856 3,872 4,384 4,408 3,920 3,432 2,448 1,464 976 1,000 32,224

Information: Layoff Hiring Inventory Totals: 25 25 32,224 Costs: $50,000 $75,000 $193,334 Cost of plan: $318,334 Planning values Starting inventory: 1000 Starting and ending workforce: 227 Hours worked per month per worker: 160 Hours per unit: 20 Hiring cost per worker: $3,000 Layoff cost per worker: $2,000 Monthly per-unit holding cost: $6

MONTH March April May June July August September October November December January February Totals Costs Hiring: Layoff: Inventory: Cost of plan:

SALES IN WORKERS NEEDED FORECASTED WORKER TO MEET SALES ACTUAL ACTUAL SALES HOURS AVERAGE = 252 WORKERS PRODUCTION 227 1,592 31,840 199 199 1,592 1,400 28,000 175 175 1,400 1,200 24,000 150 150 1,200 1,000 20,000 125 125 1,000 1,504 30,080 188 188 1,504 1,992 39,840 249 249 1,992 2,504 50,080 313 313 2,504 2,504 50,080 313 313 2,504 3,000 60,000 375 375 3,000 3,000 60,000 375 375 3,000 2,504 50,080 313 313 2,504 1,992 39,840 249 249 1,992 227 24,192 24,192

$750,000 $500,000 $72,000 $1,322,000

LAYOFFS

HIRINGS

28 24 25 25 0 0 0 0 0 0 62 64 22 250

0 0 0 0 63 61 64 0 62 0 0 0 0 250

ENDING INVENTORY 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 12,000

Information: Layoff Hiring Inventory Totals: 250 250 12,000 Costs: $500,000 $750,000 $72,000 Cost of plan: $1,322,000 Planning values Starting inventory: 1000 Starting and ending workforce: 227 Hours worked per month per worker: 160 Hours per unit: 20 Hiring cost per worker: $3,000 Layoff cost per worker: $2,000 Monthly per-unit holding cost: $6

MONTH March April May June July August September October Totals

SALES IN WORKERS NEEDED FORECASTED WORKER TO MEET SALES ACTUAL ACTUAL SALES HOURS AVERAGE = 252 WORKERS PRODUCTION 50 2,000 8,000 50 47 1,880 1,920 7,680 48 47 1,880 1,840 7,360 46 47 1,880 1,800 7,200 45 47 1,880 1,800 7,200 45 47 1,880 1,800 7,200 45 47 1,880 1,750 7,000 44 36 1,440 1,640 6,560 41 36 1,440 50 14,550 14,160

LAYOFFS

HIRINGS

3 0 0 0 0 0 11 0 0 14

0 0 0 0 0 0 0 0 14 14

ENDING INVENTORY 500 380 340 380 460 540 620 310 110 3,140

Information: Layoff Hiring Inventory Totals: 14 14 3,140 Costs: $2,800 $4,200 $12,560 Cost of plan: $19,560 Planning values Starting inventory: 500 Starting and ending workforce: 50 Hours worked per month per worker: 160 Hours per unit: 4 Hiring cost per worker: $300 Layoff cost per worker: $200 Monthly per-unit holding cost: $4 This production plan represents a mix strategy as there is a stable production for several months and then the production level changes for the final two months. The strategy is not completely level but it also does not chase the forecasted sales each month.

MONTH March April May June July August September October November December January February Totals Costs Hiring: Layoff: Inventory: Cost of plan:

$75,000 $50,000 $193,344 $318,344

LAYOFFS

HIRINGS

0 0 0 0 0 0 0 0 0 0 0 0 25 25

25 0 0 0 0 0 0 0 0 0 0 0 0 25

ENDING INVENTORY 1,000 1,424 2,040 2,856 3,872 4,384 4,408 3,920 3,432 2,448 1,464 976 1,000 32,224

The spreadsheet calculates new results for as the forecasted sales or actual workers values are changed. Besides slight formatting changes, this spreadsheet is the same as the one used to answer questions 6 and 7.

Part a.) SALES IN WORKERS NEEDED BEEFEATER DEUTSCHLANDER AGGREGATE WORKER TO MEET SALES ACTUAL ACTUAL MONTH FORECAST FORECAST FORECAST HOURS AVERAGE = 75 WORKERS PRODUCTION 20 Nov-16 650 3,048 3,698 11,834 74 75 3,750 Dec-16 676 2,899 3,575 11,440 72 75 3,750 Jan-17 624 3,198 3,822 12,230 76 75 3,750 Feb-17 624 2,671 3,295 10,544 66 75 3,750 Mar-17 696 2,919 3,615 11,568 72 75 3,750 Apr-17 475 3,102 3,577 11,446 72 75 3,750 May-17 566 2,964 3,530 11,296 71 75 3,750 Jun-17 819 2,409 3,228 10,330 65 75 3,750 Jul-17 754 3,381 4,135 13,232 83 75 3,750 Aug-17 982 3,965 4,947 15,830 99 75 3,750 20 Totals 37,422 37,500 Costs Hiring: Layoff: Inventory: Production: Cost of plan:

$16,500 $16,500 $102,870 $11,250,000 $11,385,870

Information: Starting inventory: Starting and ending workforce: Hours worked per month per worker: Production cost per unit: Hours per unit: Hiring cost per worker: Layoff cost per worker: Monthly per-unit holding cost:

LAYOFFS 0 0 0 0 0 0 0 0 0 0 55 55

ENDING HIRINGS INVENTORY 0 55 52 0 227 0 155 0 610 0 745 0 918 0 1,138 0 1,660 0 1,275 0 78 0 55 6,858

0 20 160 $300 3.2 $300 $300 $15

Part b.) SALES IN WORKERS NEEDED BEEFEATER DEUTSCHLANDER AGGREGATE WORKER TO MEET SALES ACTUAL ACTUAL MONTH FORECAST FORECAST FORECAST HOURS AVERAGE = 75 WORKERS PRODUCTION 20 Nov-19 650 3,048 3,698 11,834 74 74 3,700 Dec-19 676 2,899 3,575 11,440 72 72 3,600 Jan-20 624 3,198 3,822 12,230 76 76 3,800 Feb-20 624 2,671 3,295 10,544 66 66 3,300 Mar-20 696 2,919 3,615 11,568 72 72 3,600 Apr-20 475 3,102 3,577 11,446 72 72 3,600 May-20 566 2,964 3,530 11,296 71 71 3,550 Jun-20 819 2,409 3,228 10,330 65 65 3,250 Jul-20 754 3,381 4,135 13,232 83 83 4,150 Aug-20 982 3,965 4,947 15,830 99 99 4,950 20 Totals 37,422 37,500 Costs Hiring: Layoff: Inventory: Production: Cost of plan: Difference

$29,400 $29,400 $4,620 $11,250,000 $11,313,420 $72,450

Part c.) If hiring and layoff costs increased dramatically the level plan would be less expensive than the chase plan. This is because of the difference between the number of hirings and layoffs in the two plans. The chase plan is much more sensitive to changes in the hiring and layoff costs while the level plan is more sensitive to changes in inventory costs. However, the change in hiring and layoff costs would need to be substantial; if they both rise to $669.64 the two plans would have identical costs.

LAYOFFS 0 2 0 10 0 0 1 6 0 0 79 98

0 20 160 $300 3.2 $300 $300 $15

ENDING HIRINGS INVENTORY 0 54 2 0 27 4 5 0 10 6 -5 0 18 0 38 0 60 18 75 16 78 0 98 308

SALES REGULAR OVERTIME INVENTORY / FORECAST PRODUCTION PRODUCTION BACKORDERS 100 January 750 840 0 190 February 760 840 0 270 March 800 840 0 310 April 800 840 0 350 May 820 840 0 370 June 840 840 0 370 July 910 840 0 300 August 910 840 0 230 September 910 840 0 160 October 880 840 0 120 November 860 840 0 100 December 840 840 0 100 MONTH

CASH INFLOWS

CASH OUTFLOWS

NET FLOW

CUMULATIVE NET FLOW

$2,100,000 $2,128,000 $2,240,000 $2,240,000 $2,296,000 $2,352,000 $2,548,000 $2,548,000 $2,548,000 $2,464,000 $2,408,000 $2,352,000

$1,687,600 $1,690,800 $1,692,400 $1,694,000 $1,694,800 $1,694,800 $1,692,000 $1,689,200 $1,686,400 $1,684,800 $1,684,000 $1,684,000

$412,400 $437,200 $547,600 $546,000 $601,200 $657,200 $856,000 $858,800 $861,600 $779,200 $724,000 $668,000

$412,400 $849,600 $1,397,200 $1,943,200 $2,544,400 $3,201,600 $4,057,600 $4,916,400 $5,778,000 $6,557,200 $7,281,200 $7,949,200

Information: Cash inflow per cabinet: Regular production outflow: Overtime production outflow: Monthly inventory holding cost: When comparing this option to the mix strategy shown in Table 10.10, finance would likely select the mix strategy over the level strategy shown here. The mix strategy accumulates a higher net cash flow and does so quicker during the year than the level plan.

$2,800 $2,000 $0 $40

Part a.) MONTH January February March April May June

SALES REGULAR OVERTIME FORECAST PRODUCTION PRODUCTION 800 1000 1200 1400 1600 1500

1150 1150 1150 1150 1150 1150

0 0 0 0 150 350

ENDING INVENTORY

CASH INFLOWS

CASH OUTFLOWS

NET FLOW

0 350 500 450 200 0 0

$400,000 $500,000 $600,000 $700,000 $800,000 $750,000

$406,000 $407,500 $407,000 $404,500 $470,000 $560,000

($6,000) $92,500 $193,000 $295,500 $330,000 $190,000

Information: Cash inflow per cabinet: Regular production outflow: Overtime production outflow: Monthly inventory holding cost: b.) The net cash flows for April and May are much higher than the other months because the number of units sold is much higher than the number of units produced. The implications of building up and draining down inventory are that the production costs will remain stable, although inventory costs may be high.

CUMULATIVE NET FLOW ($6,000) $86,500 $279,500 $575,000 $905,000 $1,095,000

$500 $350 $450 $10

S&OP Spreadsheet Labor hrs. per unit: Worker hrs. per month: Beginning & ending workforce: Beginning & ending inventory:

24 150 100 100

Production cost per unit: Hiring cost: Layoff cost: Holding cost per unit per month:

$475.00 $400.00 $300.00 $3.00

Month

Sales Forecast

January February March April May June July August September October November December

500 600 700 800 900 1,000 1,000 1,100 1,200 1,300 1,400 1,500

Totals:

12,000

Sales (in labor hrs.) 12,000 14,400 16,800 19,200 21,600 24,000 24,000 26,400 28,800 31,200 33,600 36,000

Average:

Total plan cost $5,700,000 $64,000 $48,000 $3,600 $5,815,600 Grand total

Ending Actual Actual Inventory / Workers Production Hirings Layoffs Back Orders 100 100 80.0 80.00 500.00 0.00 20.00 100.00 96.0 96.00 600.00 16.00 0.00 100.00 112.0 112.00 700.00 16.00 0.00 100.00 128.0 128.00 800.00 16.00 0.00 100.00 144.0 144.00 900.00 16.00 0.00 100.00 160.0 160.00 1,000.00 16.00 0.00 100.00 160.0 160.00 1,000.00 0.00 0.00 100.00 176.0 176.00 1,100.00 16.00 0.00 100.00 192.0 192.00 1,200.00 16.00 0.00 100.00 208.0 208.00 1,300.00 16.00 0.00 100.00 224.0 224.00 1,400.00 16.00 0.00 100.00 240.0 240.00 1,500.00 16.00 0.00 100.00 100 0.00 140.00 12,000.00 160.00 160.00 1,200.00 160

Sales (in workers)

Sales & Operations Planning Spreadsheet for Kumquats Unlimited (with solver optimization) Production cost per batch: Line hours per batch: Production line hours per month: Cost to start up a line: Cost to shut down a line: Inventory holding cost: Beginning and ending lines: Beginning and ending inventory:

Month January February March April May June Total =

$2,400 16 320 hours $25,000 $6,000 $300 per batch, per month 55 production lines 100 batches

Production costs: $14,448,000 Line start-up costs: $300,000 Line shutdown costs: $72,000 Inventory holding costs: $144,000 Grand total: $14,964,000

Sales (in Actual production Production Actual Production Line Production Line lines) Lines Production Start-ups Shutdowns 55 1,000 16,000 50 55.00 1,100 0 0 1,200 19,200 60 55.00 1,100 0 0 1,200 19,200 60 55.00 1,100 0 0 1,000 16,000 50 50.00 1,000 0 5 800 12,800 40 43.00 860 0 7 800 12,800 40 43.00 860 0 0 55 12 0 6,000 6,020 12 12 Average = 50

Sales Sales Forecast (in line hours)

Ending Inventory 100 200 100 0 0 60 120 480

MONTH

SALES FORECAST

SALES IN WORKER HOURS

WORKERS NEEDED TO MEET SALES AVERAGE = 49

September-20 October-20 November-20 December-20 January-21 February-21 March-21 April-21 May-21 June-21 July-21 August-21

30,000 31,500 35,000 37,000 22,000 18,000 17,500 27,000 38,000 40,000 42,000 40,000

7,500 7,875 8,750 9,250 5,500 4,500 4,375 6,750 9,500 10,000 10,500 10,000

47 49 55 58 34 28 27 42 59 63 66 63

Totals

378,000

Costs Hiring: Layoff: Inventory: Production: Cost of plan:

$1,250 $500 $1,908,640 $28,035,840 $29,946,230

ACTUAL WORKERS 50 49 49 49 49 49 49 49 49 49 49 49 49 50

ACTUAL PRODUCTION 31,360 31,360 31,360 31,360 31,360 31,360 31,360 31,360 31,360 31,360 31,360 31,360 376,320

Question 1.) Advantages to a level production plan are that the hiring and layoff costs are very low and the company is able to meet overall sales forecast without expanding current plant capacity. Covolo could not implement a pure chase plan because capacity is currently 35,000 per month. If sales continue to grow, Covolo will need to consider how to add additional production capacity. Question 2.) Monthly S&OP updates will rolling planning horizons will help alleviate Patricia's concerns because there will be an opportunity to adjust the sales forecast every month. Significant advantages to S&OP, even though forecasts may change, include bringing marketing, operations, and finance together to agree upon the plan for the coming months and how to best handle changes in the forecast. Question 3.) I agree with David Griffin *if* the cost of retaining an employee while not producing is less or equal to the cost of a layoff plus a new hire. Holding costs of an existing employee include their salary and benefits paid, while producing an extra gauge results in materials and inventory costs. If workers are idle, the production cost per unit will increase to distribute the cost of the employee over fewer units.

LAYOFFS

HIRINGS

1 0 0 0 0 0 0 0 0 0 0 0 0 1

0 0 0 0 0 0 0 0 0 0 0 0 1 1

ENDING INVENTORY 10,000 11,360 11,220 7,580 1,940 11,300 24,660 38,520 42,880 36,240 27,600 16,960 8,320 238,580

10,000 50 160 $74.50 0.25 $1,250 $500 $8 35,000

Time units: Demand units: Time between periodic review of inventory: Order lead time: Average demand per period: Average demand during reorder period and order lead time: Standard deviation of demand during reorder period and order lead time: Percent desired service level: z value (for desired service level): Restocking level:

days tins 10 3 7 91 17 90% 1.28 113

days days tins tins tins

tins

a. 113 tins b. If standard deviation drops to 4 tins, the restocking level drops to 97 tins. Lower variability results in a lower level of safety sto c. See graph Time Inventory Level 0 113 10 0 10 113 120 20 0 20 113 100 30 0 80 30 113 40 0 60 40 113 50 0 40 50 113 60 0 20 60 113 70 0 0 70 113 0 10 20 30 40 50 80 0

Inventory Level

Cycle Stock at Jimmy's Delicatessen

Time

Jimmy's Delicatessen

Time

a.) Time units: Demand units: Time between periodic review of inventory: Average order lead time: Average demand during reorder period and order lead time: Standard deviation of demand during reorder period and order lead time: Percent desired service level: z value (for desired service level): Restocking level:

days meals 5 2 100 20 90% 1.28 126

Percent desired service level: z value (for desired service level): Restocking level:

95% 1.65 133

Restocking level: Current Inventory: Number to order:

126 20 106

b.)

days days meals meals

meals

Annual demand: Annual holding cost, per unit: Cost per order: Economic order quantity:

16000 $2.50 $50.00 800

Annual demand: Annual holding cost, per unit: Cost per order: Economic order quantity:

32000 $2.50 $50.00 1131

No, the EOQ does not double as the annual demand doubles. The EOQ increases by the square-root of two if demand doubles.

Annual demand: Annual holding cost, per unit: Cost per order: Discount cost per order: Cost per unit: Discount cost per unit:

16000 $2.50 $50.00 $50.00 $50.00 $45.00

Discount order quantity: 1500 Discounted total cost of units: $720,000.00 Discount annual holding cost: $1,875.00 Discount annual ordering cost: $533.33 Total cost: $722,408.33 Economic order quantity: 800 Total cost of units: $800,000.00 EOQ annual holding cost: $1,000.00 EOQ annual ordering cost: $1,000.00 Total cost: $802,000.00 Total savings under EOQ: -$79,591.67 Pam should order 1500 at a time to take advantage of the lower cost per unit. Even though it's not the EOQ, ordering 1500 units per order will result in a total annual savings of $79,591.67.

Annual demand: Annual holding cost, per unit: Cost per order: Economic order quantity:

1200 $15.00 $200.00 179

Annual demand: Annual holding cost, per unit: Cost per order: Discount cost per order: Cost per unit: Discount cost per unit:

1200 $15.00 $200.00 $200.00 $50.00 $42.00

Discount order quantity: 201 Discounted total cost of units: $50,400.00 Discount annual holding cost: $1,507.50 Discount annual ordering cost: $1,194.03 Total cost: $53,101.53 Economic order quantity: 179 Total cost of units: $60,000.00 EOQ annual holding cost: $1,342.50 EOQ annual ordering cost: $1,340.78 Total cost: $62,683.28 Total savings under EOQ: -$9,581.75 KraftyCity should order 201 at a time to take advantage of the lower cost per unit. Ordering 201 units per order will result in a total annual savings of $9581.75.

Time units: weeks Demand units: workbenches Average order lead time: 3 weeks Standard deviation of lead time: 1.2 weeks Average demand during time unit: 24 workbenches Standard deviation of demand during time unit: 8 workbenches Percent desired service level: 95% z value (for desired service level): 1.65 Reorder point: 125 workbenches

Time units: weeks Demand units: workbenches Average order lead time: 3 weeks Standard deviation of lead time: 0 weeks Average demand during time unit: 24 workbenches Standard deviation of demand during time unit: 8 workbenches Percent desired service level: 95% z value (for desired service level): 1.65 Reorder point: 95 workbenches Reorder point is lower because there is no variance to the order lead time. This lowers safety stock required by 30 workbenches.

Annual demand: Annual holding cost, per unit: Cost per order: Economic order quantity:

4000 $2.00 $15.00 245

Annual demand: Annual holding cost, per unit: Cost per order:

4000 $2.00 $15.00

Order quantity Annual holding cost: Annual ordering cost: Total cost:

200 $200.00 $300.00 $500.00

Time units: Demand units: Average order lead time: Standard deviation of lead time: Average demand during time unit: Standard deviation of demand during time unit: Percent desired service level: z value (for desired service level): Reorder point:

weeks bags 2 0 80 16 95% 1.65 198

weeks weeks bags bags

bags

Time units: Demand units: Time between periodic review of inventory: Average order lead time: Average demand per period: Standard deviation of demand per period: Average demand during reorder period and order lead time: Standard deviation of demand during reorder period and order lead time: Percent desired service level: z value (for desired service level): Restocking level:

weeks bags 1 2 80 16 240 28 95% 1.65 287

weeks weeks bags bags bags bags

bags

Note: The answer assumes that the replenishment lead time is still 2 weeks. IF the vendor were to immediately restock from his delivery truck, then the restocking level would drop to 107 units. We can quickly show this by plugging in 0 for the "average order lead time" above.

Annual demand: Annual holding cost, per unit: Cost per order: Discount cost per order: Cost per unit: Discount cost per unit:

630 $2.00 $9.00 $9.00 $6.00 $4.50

Discount order quantity: 101 Discounted total cost of units: $2,835.00 Discount annual holding cost: $101.00 Discount annual ordering cost: $56.14 Total cost: $2,992.14 a.) Economic order quantity: 75 Total cost of units: $3,780.00 EOQ annual holding cost: $75.00 EOQ annual ordering cost: $75.60 Total cost: $3,930.60 Total savings under EOQ: -$938.46 b.) Ollah should order 101 bags at a time to take advantage of the lower cost per unit. Ordering 101 units per order will result in a total annual savings of $938.46. The optimal order quantity is higher than EOQ because of the amount of the discount. c.) Time units: Demand units: Average order lead time: Standard deviation of lead time: Average demand during time unit: Standard deviation of demand during time unit: Percent desired service level: z value (for desired service level): Reorder point:

weeks bags 2 0 12.6 3.2 98% 2.05 35

weeks weeks bags bags

bags

Item: Value of item if demanded: Item cost: Disposal cost: Salvage value: Shortage cost: Excess cost: Target service level: Mean demand: Standard deviation of mean demand: Standard deviations above the mean: Target stocking point:

t-shirts $20.00 $6.50 $0.00 $3.00 $13.50 $3.50 79% 120 35 0.81 149

t-shirts t-shirts t-shirts

SIDE NOTE: We can also quickly calculate the target stocking point using the NORMINV function for Excel. It works like this: =NORMINV(target service level, mean, standard deviation" = NORMINV(0.79,120,35) = 148.22 This target service level is 149, which is (149-120)/35 = 0.81 standard deviations above the mean demand level

ve the mean demand level

a.) Item: Value of item if demanded: Item cost: Disposal cost: Salvage value: Shortage cost: Excess cost: Target service level: Target stocking point: STUDENTS WHO BOUGHT A BOOK 16 17 18 19 20 21 22 23 24 25

books $50.00 $12.00 $0.00 $0.00 $38.00 $12.00 76% 21

PERCENTAGE OF OBSERVATIONS 0% 4% 15% 17% 18% 26% 10% 6% 4% 0%

books CUMULATIVE PERCENTAGE 0% 4% 19% 36% 54% 80% 90% 96% 100% 100%

b.) Item: Value of item if demanded: Item cost: Disposal cost: Salvage value: Shortage cost: Excess cost: Target service level: Target stocking point: STUDENTS WHO BOUGHT A BOOK 16 17 18 19 20 21 22 23 24 25

books $50.00 $22.00 $0.00 $0.00 $28.00 $22.00 56% 20

PERCENTAGE OF OBSERVATIONS 0% 4% 15% 17% 18% 26% 10% 6% 4% 0%

books CUMULATIVE PERCENTAGE 0% 4% 19% 36% 54% 80% 90% 96% 100% 100%

The target service level and target stocking point decreased because the cost of printing each book increased, thus increasing the excess cost and decreasing the shortage cost.

Annual demand: Annual holding cost, per unit: Cost per order: Cost per unit:

3120 $48.00 $2.00 $120.00

Economic order quantity:

EOQ annual holding cost: EOQ annual ordering cost: Total holding and ordering cost:

$384.00 $390.00 $774.00

a.)

b.)

The annual holding costs and ordering costs are roughly equal. They would be identical if we could somehow order a fractional number of printers as dictated by the EOQ formula.

c.) Current order quantity: Current annual holding cost: Current annual ordering cost: Total holding and ordering cost:

120 $2,880.00 $52.00 $2,932.00

Order quantity: Annual holding cost: Annual ordering cost: Total holding and ordering cost:

12 $288.00 $520.00 $808.00

Total savings:

$2,124.00

d.) Time units: Demand units: Average order lead time: Standard deviation of lead time: Average demand during time unit: Standard deviation of demand during time unit: Percent desired service level: z value (for desired service level): Reorder point: Safety stock:

weeks printers 3 0 60 12 99% 2.33 229 49

weeks weeks printers printers

printers printers

e.) Order quantity: Safety Stock: Annual holding cost, per unit: Annual inventory holding cost: Annual safety stock holding cost:

120 49 $48.00 $5,232.00 $2,352.00

Order quantity: Safety Stock: Annual holding cost, per unit: Annual inventory holding cost: Annual safety stock holding cost:

120 28 (we can verify this by plugging 1 into the "average order lead time" above $48.00 $4,224.00 $1,344.00

Savings in annual holding costs:

$1,008.00

f.)

If OfficeMax takes this step into the 21st century they will realize that as the cost of placing an order decreases, so does the EOQ. As the EOQ decreases, average inventory level will decrease, and so will holding costs for the year. Finally, since ordering costs and holding costs for the year are equal under the EOQ, we can also see that ordering costs will fall as well. Long story short -- good news all-around! Perhaps Officemax would be a wholly separate entity from Office Depot had they made this move a little sooner.

Annual demand: Annual holding cost, per unit: Cost per order: Cost per unit:

15376 $256.00 $25.00 $640.00

Economic order quantity: EOQ annual holding cost: EOQ annual ordering cost: Total holding and ordering cost:

55 $7,040.00 $6,989.09 $14,029.09

a.)

b.) Time units: Demand units: Average order lead time: Standard deviation of lead time: Average demand during time unit: Standard deviation of demand during time unit: Percent desired service level: z value (for desired service level): Reorder point: Safety stock:

weeks monitors 2 0.3 307.52 16 95% 1.65 772 157

weeks weeks monitors monitors

monitors monitors

c.) Order quantity: Annual holding cost: Annual ordering cost: Total holding and ordering cost:

64 $8,192.00 $6,006.25 $14,198.25

d.) As the annual holding cost per monitor increases, the EOQ will decrease. This is because the ratio of holding cost to order cost will increase.

e.) Order quantity: Safety Stock: Annual holding cost, per unit: Annual inventory holding cost: Annual safety stock holding cost: Total annual holding cost (including safety stock):

64 157 $256.00 $48,384.00 $40,192.00 $88,576.00

weeks monitors 1 0 307.52 16 95% 1.65 334 27

Order quantity: Safety Stock: Annual holding cost, per unit: Annual inventory holding cost: Annual safety stock holding cost: Total annual holding cost (including safety stock):

64 27 $256.00 $15,104.00 $6,912.00 $22,016.00

Savings in annual holding costs:

$66,560.00

f.)

weeks weeks monitors monitors

monitors monitors

a.) SLOW SEASON Annual demand: Annual holding cost, per unit: Cost per order: Economic order quantity:

7800 $12.00 $5.00 81

BUSY SEASON Annual demand: Annual holding cost, per unit: Cost per order: Economic order quantity:

15600 $12.00 $5.00 114

b.) Order quantity: 150 Annual holding cost: $900.00 Annual ordering cost: $390.00 Total holding and ordering cost: $1,290.00

weeks cases 0.5 0 325 5.25 98% 2.05 171

weeks weeks cases cases

cases

Annual demand: Annual holding cost, per unit: Cost per order: Discount cost per order: Cost per unit: Discount cost per unit:

2000 $2.00 $15.00 $15.00 $7.00 $6.50

Discount order quantity: 501 Discounted total cost of units: $13,000.00 Discount annual holding cost: $501.00 Discount annual ordering cost: $59.88 Total cost: $13,560.88 Economic order quantity: 174 Total cost of units: $14,000.00 EOQ annual holding cost: $174.00 EOQ annual ordering cost: $172.41 Total cost: $14,346.41 Total savings under EOQ:

-$785.53

Dave's Sporting Goods should order 501 at a time to take advantage of the lower cost per unit. Ordering 501 units per order will result in a total annual savings of $785.53.

Calculating Savings under EOQ Annual demand: Annual holding cost, per unit: Cost per order:

4000 $30.00 $30.00

Current order quantity: 500 Current annual holding cost: $7,500.00 Current annual ordering cost: $240.00 Total cost: $7,740.00 Economic order quantity: 89.44 EOQ annual holding cost: $1,341.64 EOQ annual ordering cost: $1,341.64 Total cost: $2,683.28 Total savings under EOQ: $5,056.72

Calculating Savings Due to Pooling Safety Stock Annual holding cost per unit: Lead time (fixed): Percent desired service level: z value (for desired service level):

$5.00 8 days 99% 2.33

Location 1 Location 2 Location 3

Average daily demand 50 40 30

Variance of daily demand 4.5 6.2 5

Pooled SS

Average daily demand 120

Variance of daily demand 15.7

Average demand during Reorder point lead time 413.98 400 336.41 320 254.74 240 Total units: Total annual holding cost:

Safety stock 13.98 16.41 14.74 45.13 $225.63

Average demand during Reorder point lead time 986.11 960 Total annual holding cost:

Safety stock 26.11 $130.56

Savings due to pooling safety stock:

$95.07

Question 1.) FB378 Annual demand: Annual holding cost, per unit: Cost per order: Cost per unit: Economic order quantity: Average order lead time: Standard deviation of lead time: Average demand during time unit: Standard deviation of demand during time unit: Percent desired service level: z value (for desired service level): Reorder point:

1916 $1.00 $35.00 $5.00 367 3 0 36.85 7.91 95% 1.65 134

Annual demand: Annual holding cost, per unit: Cost per order: Cost per unit: Economic order quantity: Average order lead time: Standard deviation of lead time: Average demand during time unit: Standard deviation of demand during time unit: Percent desired service level: z value (for desired service level): Reorder point:

Question 2.) Current order quantity: 120 Current annual holding cost: $60.00 Current annual ordering cost: 558.8333 Total holding and ordering cost: $618.83

Current order quantity: Current annual holding cost: Current annual ordering cost: Total holding and ordering cost:

Economic order quantity: 367 EOQ annual holding cost: 183.5 EOQ annual ordering cost: 182.7248 EOQ total holding and ordering cost: $366.22

Economic order quantity: EOQ annual holding cost: EOQ annual ordering cost: EOQ total holding and ordering cost:

Total savings using EOQ:

$252.61

Question 3.) There is no single right answer to this question. They should be included as a cost of poor service quality, as a lost revenue, and as service quality improves so the demand will increase. The increase in demand will effect the EOQ from question 1, but this number can be easily calculated using the new average demand.

Total savings using EOQ:

GS131 Annual demand: al holding cost, per unit: Cost per order: Cost per unit: conomic order quantity:

2480 $2.15 $15.00 $10.75 187

verage order lead time: d deviation of lead time: emand during time unit: emand during time unit: nt desired service level: r desired service level): Reorder point:

6 0 47.69 12.78 95% 1.65 338

Current order quantity: 850 ent annual holding cost: $913.75 nt annual ordering cost: 43.76471 ding and ordering cost: $957.51

conomic order quantity: 187 OQ annual holding cost: 201.025 Q annual ordering cost: 198.9305 ding and ordering cost: $399.96

al savings using EOQ:

$557.56

On-hand inventory at end of week 1 Week 2 Forecasted demand 45 Booked orders 15 Projected ending inventory 170 Master production schedule 150 Available to promise 52

65 3 50 100 70

4 55 48 15

5 60 25 155 200 81

6 65 72 83

7 70 22 13

8 75 67 88 150 73

9 80 10 8

On-hand inventory at end of week 1 Week 2 Forecasted demand 45 Booked orders 15 Projected ending inventory 170 Master production schedule 150 Available to promise 42

65 3 50 100 70

4 55 58 12

5 60 25 152 200 81

6 65 72 80

The company may want to increase production to meet forecasted demand.

7 70 22 10

8 75 67 85 150 73

9 80 10 5

On-hand inventory at end of week 1 Week 2 Forecasted demand 250 Booked orders 265 Projected ending inventory 335 Master production schedule 500 Available to promise 80

100 3 250 255 80

4 300 270 380 600 85

5 300 245 80

6 350 260 430 700 205

7 350 235 80

8 250 180 330 500 220

9 250 100 80

On-hand inventory at end of week 1 Week 2 Forecasted demand 250 Booked orders 265 Projected ending inventory 335 Master production schedule 500 Available to promise 80

100 3 250 255 80

4 300 270 380 600 85

5 300 245 80

6 350 260 330 600 105

7 350 235 -20

A negative projected ending inventory value suggests that more production may be needed if the sales forecasts are accurate. A negative available-to-promise number means that you have over-sold your available inventory and will either need to manufacture/purchase additional units or have backorders. As a manager, a negative projected ending inventory is much easier to deal with.

8 250 180 230 500 220

9 250 100 -20

a.) On-hand inventory at end of April: 40 Month ************May*********** Week 19 20 21 22 Forecasted demand 200 200 200 225 Booked orders 205 203 201 195 Projected ending inventory 435 232 31 481 Master production schedule 600 675 Available to promise 31 97

************June************ 23 24 25 26 225 225 200 200 193 190 182 178 256 31 431 231 600 240

b.) The following two statements are true: "The ATP for week 25 will increase by 50 units", "The ATP for weeks 19 and 22 will be unaffected". The following statement is false: "The projected ending inventory for week 25 will increase by 50 units".

***A2*** LT (weeks):

Min. order:

Gross requirements Scheduled receipts Projected ending inventory: Net requirements Planned receipts Planned orders

Week:

1 200

260

60 0 0 140

2 200 200 60 0 0 300

3 200

4 300

5 300

6 300

0 140 140 300

0 300 300 300

0 300 300 0

***A2*** LT (weeks):

Min. order:

Gross requirements Scheduled receipts Projected ending inventory: Net requirements Planned receipts Planned orders

Week:

1 200

260

60 0 0 440

2 200 200 60 0 0 300

3 200

4 300

5 300

6 300

-140 140 0 300

0 440 440 0

0 300 300 0

Based on a 3 week lead time, the company can not support the current gross requirements for A2. The current inventory can not fulfill the requirement until the first planned receipt could arrive (in 3 weeks). The implications of having reliable supplier and manufacturer lead times are that without them you are unable to plan on fulfilling your production requirements.

***B3***

Week:

2 400

3 400

4 400

6 400

0 0 0 900

500 400 900 0

100 0 0 900

600 300 900 0

600 0 0 0

200 0 0 0

Gross requirements LT (weeks): 1 Scheduled receipts Projected ending inventory: Net requirements Min. order: 900 Planned receipts Planned orders Average inventory over the 6 weeks:

333.33

***B3***

Week:

2 400

3 400

4 400

6 400

0 0 0 400

0 400 400 400

0 400 400 0

0 0 0 400

0 400 400 0

Gross requirements LT (weeks): 1 Scheduled receipts Projected ending inventory: Net requirements Min. order: 300 Planned receipts Planned orders Average inventory over the 6 weeks:

0.00

The implications for minimum order quantities in the MRP environment are that a high minimum order quantity may result in having to hold and manage inventory and incur inventory holding costs.

Acme PolyBob LT (weeks): Item B # Required: LT (weeks):

1 1

Min. order:

Item C # Required: LT (weeks):

2 3

Min. order:

500

Item E # Required: LT (weeks):

5 4

Min. order:

Item F # Required: LT (weeks):

Min. order:

Gross requirements Scheduled receipts Projected ending inventory: Net requirements Planned receipts Planned orders

Gross requirements Scheduled receipts Projected ending inventory: Net requirements 5000 Planned receipts Planned orders

3 5

750

Week:

1 0 0

2 250 250

3 300 300

4 300 300

5 300 300

6 200 200

Week:

1 0

2 250

3 300

4 300

5 300

6 200

0 0 0 250

0 250 250 300

0 300 300 300

0 300 300 200

0 200 200 0

Week:

1 0

5 600

6 400

0 0 0 600

3 600 600 0 0 0 500

4 600

2 500 500 0 0 0 600

0 600 600 0

100 400 500 0

Week:

1 2 3 1350 1500 1400

4 900

5 600

6 0

5750

4400 2900 1500 0 0 0 0 0 0 0 0 0

600 0 0 0

0 0 0 0

Week:

1 2 3 1450 1500 1300

4 300

5 200

6 0

4750

3300 1800 0 0 0 0 0 0

200 0 0 0

0 0 0 0

MPS due date Start assembly

Gross requirements Scheduled receipts Projected ending inventory: Net requirements Planned receipts Planned orders

500 0 0 0

Broadcast Spreader MPS due date LT (weeks): 0 Start assembly

Week:

Gear and rotor plate assembly # Required: 1 Gross requirements LT (weeks): 1 Scheduled receipts Projected ending inventory: Net requirements Min. order: 2500 Planned receipts Planned orders

Week:

Wheels 2 Gross requirements 1 Scheduled receipts Projected ending inventory: Net requirements 1 Planned receipts Planned orders

Week:

Cotter Pins 2 Gross requirements 3 Scheduled receipts Projected ending inventory: Net requirements 15000 Planned receipts Planned orders

Week:

# Required: LT (weeks):

Min. order:

# Required: LT (weeks):

Min. order:

1000

2 2000 2000

4 2000 2000

6 2000 2000

1 0

2 2000

3 0

4 2000

5 0

6 2000

1000 1500 1500 2000 2000 0 1000 0 500 0 0 2500 0 2500 0 2500 0 2500 0 0 1 0

2 4000

3 0

4 4000

5 0

0 0 0 0 6 4000

0 0 0 0 0 0 0 4000 0 4000 0 4000 0 4000 0 4000 0 4000 4000 0 4000 0 4000 0 1 2 3 4 2500 2000 2500 2000

5 0

11000 8500 6500 4000 2000 2000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

6 2000 0 0 0 0

Triam Deluxe Computer System MPS due date LT (weeks): 0 Start assembly

Week:

System unit # Required: 1 Gross requirements LT (weeks): 1 Scheduled receipts Projected ending inventory: Net requirements Min. order: 1 Planned receipts Planned orders

2 2500 2500

3 4 5 6 3000 3000 3000 2000 3000 3000 3000 2000

Week:

1 0

2 2500

3 4 5 6 3000 3000 3000 2000

0 0 0 2500

0 2500 2500 3000

0 0 0 0 3000 3000 3000 2000 3000 3000 3000 2000 3000 3000 2000 0

Speakers 2 Gross requirements 1 Scheduled receipts Projected ending inventory: Net requirements 5000 Planned receipts Planned orders

Week:

1 0 5000 5000 0 0 0

2 5000

3 4 5 6 6000 6000 6000 4000

0 0 0 6000

0 0 0 1000 6000 6000 6000 4000 6000 6000 6000 5000 6000 6000 5000 0

CD-ROM drives # Required: 1 Gross requirements LT (weeks): 6 Scheduled receipts Projected ending inventory: Net requirements Min. order: 5000 Planned receipts Planned orders

Week:

1 0

2 2500

3 4 5 6 3000 3000 3000 2000

13500

13500 0 0 0

11000 0 0 0

8000 5000 2000 0 0 0 0 0 0 0 0 0

# Required: LT (weeks):

Min. order:

0 0 0 0

a.) On-hand at end of December: Month Week Forecasted demand Booked orders Projected ending inventory Master production schedule Available to promise

916 ************January************ 1 2 3 4 1000 1000 1250 1250 1095 950 1100 963 3071 2071 821 3821 3250 4250 1021 1067

************February************ 5 6 7 8 1500 1500 1750 1750 1125 1095 1243 1208 2321 821 2571 821 3500 1049

b.) According to the available-to-promise numbers, Baxter can ship 1021 of the doses in week 1 and the remaining 979 doses in week 4.

c.) In order to ship additional doses to the hospital Baxter would need to contact some of their other customers and prioritize which of them will receive fewer doses than originally ordered.

Vaxidene (4mg = 1 dose) MPS doses due MPS mg due LT (weeks): 1 Start mixing

Week:

1 0 0 0

2 0 0 0

3 4 0 4250 0 17000 17000 0

5 0 0 0

6 7 0 3500 0 14000 14000 0

Compound X # Required: 0.5 LT (weeks): 1

Min. order:

Week: 1 2 3 4 5 6 7 Gross requirements 0 0 8500 0 0 7000 0 Scheduled receipts Projected ending inventory: 1500 1500 1500 13000 13000 13000 6000 6000 Net requirements 0 0 7000 0 0 0 0 20000 Planned receipts 0 0 20000 0 0 0 0 Planned orders 0 20000 0 0 0 0 0

Compound Y Week: 1 2 3 4 5 # Required: 0.25 Gross requirements 0 0 4250 0 0 LT (weeks): 1 Scheduled receipts Projected ending inventory: 1000 1000 1000 1750 1750 1750 Net requirements 0 0 3250 0 0 Min. order: 5000 Planned receipts 0 0 5000 0 0 Planned orders 0 5000 0 0 5000

6 3500

Compound Z Week: 1 # Required: 0.25 Gross requirements 0 LT (weeks): 1 Scheduled receipts 200 Projected ending inventory: 0 200 Net requirements 0 Min. order: 1 Planned receipts 0 Planned orders 0

6 3500

7 0

2 0

5 0

7 0

3250 3250 1750 0 5000 0 0 0

3 4250

4 0

200 0 0 4050 0 4050 4050 0

0 0 0 0

0 0 0 3500 0 3500 3500 0

0 0 0 0

4 0

5 2500

7 0

Compound A Week: 1 2 # Required: 0.375 Gross requirements 0 12500 LT (weeks): 1 Scheduled receipts Projected ending inventory: 500 500 0 Net requirements 0 12000 Min. order: 9500 Planned receipts 0 12000 Planned orders 12000 0

3 0

Compound B Week: 1 2 # Required: 0.25 Gross requirements 0 10000 LT (weeks): 1 Scheduled receipts Projected ending inventory: 0 0 0 Net requirements 0 10000 Min. order: 4000 Planned receipts 0 10000 Planned orders 10000 0

3 0

4 0

5 0

6 0

7 0

0 0 0 0

Compound C Week: 1 2 # Required: 0.25 Gross requirements 0 4525 LT (weeks): 1 Scheduled receipts Projected ending inventory: 0 0 0 Net requirements 0 4525 Min. order: 2000 Planned receipts 0 4525 Planned orders 4525 0

3 0

4 0

5 4250

6 0

7 0

0 0 0 4250 0 4250 4250 0

0 0 0 0

Compound D Week: 1 2 # Required: 0.125 Gross requirements 0 2025 LT (weeks): 1 Scheduled receipts Projected ending inventory: 3000 3000 975 Net requirements 0 0 Min. order: 1 Planned receipts 0 0 Planned orders 0 0

3 0

4 0

5 1750

6 0

7 0

975 0 0 0

975 0 0 775

0 775 775 0

0 0 0 0

6 0

0 7000 7000 7000 0 2500 0 0 0 9500 0 0 9500 0 0 0

JOB A B C D

PAINTING 1.5 4 3 6

Estimated Days ASSEMBLY PACKING 2 0.5 3 1 2 0.5 4 1

TOTAL TASK DAYS UNTIL TIME DUE 4 15 8 16 5.5 8 11 20

CRITICAL RATIO 3.75 2.00 1.45 1.82

First come - first served PAINTING JOB START END A 0 1.5 B 1.5 5.5 C 5.5 8.5 D 8.5 14.5

ASSEMBLY START END 1.5 3.5 5.5 8.5 8.5 10.5 14.5 18.5

PACKING START END DAYS LATE 3.5 4 0 8.5 9.5 0 10.5 11 3 18.5 19.5 0 Average lateness: 0.75

Earliest due date PAINTING JOB START END C 0 3 A 3 4.5 B 4.5 8.5 D 8.5 14.5

ASSEMBLY START END 3 5 5 7 8.5 11.5 14.5 18.5

PACKING START END DAYS LATE 5 5.5 0 7 7.5 0 11.5 12.5 0 18.5 19.5 0 Average lateness: 0

ASSEMBLY START END 3 5 9 13 13 16 16 18

PACKING START END DAYS LATE 5 5.5 0 13 14 0 16 17 1 18 18.5 3.5 Average lateness: 1.125

Critical ratio JOB C D B A

PAINTING START END 0 3 3 9 9 13 13 14.5

Earliest due date performs best, as it enables all jobs to be completed on-time. The implications are that the jobs that ask for the tightest deadlines get priority over the jobs that are willing to wait. This could be unfair to the jobs that come in earlier and have to wait.

JOB A B C D

NAME Uptown Gallery High Museum Chester College Smith

STEP 1 3 5 3 6

Estimated Days STEP 2 2 2 2 4

STEP 3 3.5 1 5 1

TOTAL TASK DAYS UNTIL TIME DUE 8.5 21 8 15 10 14 11 15

CRITICAL RATIO 2.47 1.88 1.40 1.36

Critical ratio JOB D C B A

NAME Smith Chester College High Museum Uptown Gallery

STEP 1 START END 0 6 6 9 9 14 14 17

STEP 2 START END 6 10 10 12 14 16 17 19

STEP 3 START END DAYS LATE 10 11 0 12 17 3 17 18 3 19 22.5 1.5 Average lateness: 1.875

The new sequence using the critical ratio rule will be D, C, B, A. If Carlos's uses the critical ratio rule to sequence these jobs, 3 of them will be late.

Minneapolis Distribution Center Month: Week: Gross requirements LT (weeks): 2 Scheduled receipts Projected ending inventory: Net requirements Min. order: 120 Planned receipts Planned orders

160

45 80

November 46 47 80 80

48 80

49 90

December 50 51 90 100

52 100

1 120

January 2 3 120 140

4 140

80 0 0 120

0 0 0 120

40 80 120 120

80 40 120 0

110 10 120 120

20 0 0 120

40 80 120 120

60 60 120 120

40 80 120 0

20 100 120 0

November 46 47 60 70

48 70

49 80

December 50 51 80 80

52 80

1 90

January 2 3 90 95

4 95

5 0 0 100

35 65 100 100

65 35 100 100

85 15 100 0

5 0 0 100

25 75 100 100

45 55 100 100

55 45 100 100

65 35 100 100

75 25 100 0

November 46 47 220 220

48 100

49 120

December 50 51 220 220

52 220

257 340 340

Buffalo Distribution Center Month: Week: Gross requirements LT (weeks): 1 Scheduled receipts Projected ending inventory: Net requirements Min. order: 100 Planned receipts Planned orders

45 60 100 65 0 0 0

Master Schedule Month: Week: Total planned orders Booked orders Projected ending inventory Master production schedule Available to promise

45 120 120 257 340 257

137 320 320

257 440 440

70 30 100 100

Question 1.) Week: Total planned orders Booked orders Projected ending inventory Master production schedule Available to promise

7000

1 2 3 4 5 6 7 8 20000 20000 20000 20000 20000 20000 20000 20000 23500 23000 21500 15050 13600 11500 5400 1800 23500 500 19000 -1000 19000 -1000 19000 -1000 40000 40000 40000 40000 500 3450 14900 32800

Realco is showing negative projected inventory but still has some breadmakers available-to-promise. They have not yet "overpromised" but it looks as if they may run into this problem soon. In my view, Realco should revisit their forecast and then evaluate the options for changing production to reflect demand. Question 2.) Jack's approach to order promising has been serving as a "rule-of-thumb" in the absence of any real information. The advantages are that even without data, he has been able to give customers a fairly reliable estimate of the time it will take to receive their order. The disadvantage is that as the demand increases and the company fails to update planned order forecasts or the master production schedule, this rule-of-thumb will fail. Formal master scheduling would allow the company to see how many units will be produced vs. ordered and know how many can be promised to customers placing orders. Organizationally, there would need to be communication and commitment between marketing, sales, manufacturing, and other groups to ensure everyone participates in the new plan. Question 3.) Refusing a customer order up-front when you know that you can not deliver is a responsible and honest action. Accepting an order that you know you will be unable to deliver is unethical. The implications for master scheduling is that when units are promised that are unavailable is that some customers will not receive their promised orders, the master schedule can be used to see how many units are short and when the backorder can be filled. Question 4.) Week: Total planned orders Booked orders Projected ending inventory Master production schedule Available to promise

7000

Original average inventory level: New average inventory level:

1 2 3 4 5 6 7 8 20000 20000 20000 20000 20000 20000 20000 20000 23500 23000 21500 15050 13600 11500 5400 1800 3500 500 -1000 -1000 -1000 -1000 -1000 -1000 20000 20000 20000 20000 20000 20000 20000 20000 3500 -3000 -1500 4950 6400 8500 14600 18200 9750 -250

We must be careful when interpreting these numbers since inventory can't really be negative. However, using our intuition we can see that making smaller batches more often will lower inventory levels.

Demand rate: Lead Time: Container capacity: Safety factor:

750 40 1000 10%

Kanban cards required:

units per hour hours units

The number of Kanban cards required is 33; Choice D.

Demand rate: Lead Time: Container capacity: Safety factor:

200 12 144 15%

units per hour hours units

Kanban cards required:

Equivalents:

2880 14.4

units hours' worth of units

Demand rate: Lead Time: Container capacity: Safety factor: Kanban cards required: Equivalents:

200 12 72 15% 39 2808 14.04

units per hour hours units

a.)

b.)

c.)

units hours' worth of units

Yes, but only slightly. Reducing the size of the container results in fewer units of inventory in the system.

Demand rate: Lead Time: Container capacity: Safety factor:

300 4 40 10%

units per hour hours units

Kanban cards required:

Equivalents:

1320 4.4

units hours' worth of units

Demand rate: Lead Time: Container capacity: Safety factor: Kanban cards required: Equivalents:

300 3 40 10% 25 1000 3.33

units per hour hours units

a.)

b.)

c.)

units hours' worth of units

Yes, reducing the lead time will result in fewer units of inventory in the system.

Demand rate: Lead Time: Container capacity: Safety factor:

1000 2 250 15%

units per hour hours units

Kanban cards required:

Equivalents:

2500 2.5

units hours' worth of units

Demand rate: Lead Time: Container capacity: Safety factor: Kanban cards required: Equivalents:

1000 2 250 0% 8 2000 2.00

units per hour hours units

a.)

b.)

c.)

units hours' worth of units

No, eliminating the safety factor would probably not be a wise thing to do.

Demand rate: Lead Time: Container capacity: Safety factor:

60 40 20 10%

units per hour hours units

Kanban cards required:

132

Equivalents:

2640 44

units hours' worth of units

Demand rate: Lead Time: Container capacity: Safety factor: Kanban cards required: Equivalents:

120 20 20 10% 132 2640 22.00

units per hour hours units

a.)

b.)

c.)

units hours' worth of units

No, doubling demand rate while cutting the lead time in half will not make any difference in inventory level.

Using MRP Planned Orders to Determine the Number of Kanban Production Cards Needed Hours per week: Production lead time (T): Container size (C): These labels are swapped Safety factor (x):

40 3 300 5%

Planned orders (from MRP):

1 15,000

2 16,000

3 15,000

WEEK 4 15,000

5 14,500

6 14,000

7 13,000

Hourly demand (D):

375

400

375

362.5

350

325

# of production cards (not rounded): # of production cards (rounded up):

3.94 4

4.20 5

3.94 4

3.81 4

3.68 4

3.41 4

Hours' worth of inventory:

3.20

3.00

3.20

3.31

3.43

3.69

hours

1. Some of the key advantages of the Japanese automotive supply chain were a) its leanness in terms of inventory, which helped keep costs low, b) the emphasis on a few, key suppliers, which help firms focus their quality improvement efforts, and c) an emphasis on waste reduction. Running supply chains with very little inventory works fine as long as there aren't *major* interruptions. When such interruptions do occur, supply chain participants have to react more quickly and decisively than they would if there were large buffers of inventory. 2. The push toward standardization of parts and more autonomous supply sources for each region are consistent with lean. But what about higher inventory levels? One could argue that higher inventory is inconsistent with lean, but a more sophisticated view is that it's not inventory per se that is bad, but *too much* inventory. If Toyota decides to set inventory levels in a logical manner that better balances the costs of holding versus running out, this is not necessarily inconsistent with lean thinking. 3. In addition to the above strategies, Toyota and other manufacturers might also try working with competitors to establish inventory or capacity "pools" that can be tapped into in case of severe interruptions. For example, Toyota and Honda might jointly invest in a facility capable of making certain parts if there is a supply chain disruption. That way, neither party would have to bear the full expense. 4. If Toyota asks its upstream suppliers to keep more safety stock inventory, then Toyota has to be willing to pay for the added protection. Toyota will also need to work closely with suppliers to identify what the "right" levels of safety stock are.

ts leanness in terms of which help firms focus their upply chains with very little terruptions do occur, supply ere were large buffers of

s for each region are hat higher inventory is se that is bad, but *too t better balances the costs

try working with case of severe interruptions. certain parts if there is a

Toyota has to be willing to to identify what the "right"

a.)

A, 3

C, 6

E, 2.5

B, 2

D, 1.5

F, 3.5

G, 4

NOTE: Enter values from the problem into the yellow highlighted columns to find the solution: ACTIVIT CRITICAL Y DURATION (DAYS) PREDECESSORS ES EF LS LF PATH? A 3 None 0 3 0 3 YES B 2 None 0 2 4.5 6.5 C 6 A 3 9 3 9 YES D 1.5 A B 3 4.5 6.5 8 E 2.5 C D 9 11.5 9 11.5 YES F 3.5 D 4.5 8 8 11.5 G 4 E F 11.5 15.5 11.5 15.5 YES b.) Paths: A-C-E-G A-D-E-G A-D-F-G B-D-E-G B-D-F-G

Length: 15.5 11 12 10 11

c.) The critical activities are A-C-E-G as they are the ones that make up the critical path. The entire project will take 15.5 days. d.) No, crashing activity C from 6 days down to 2 days will only reduce the total project to 12 days (the goal is less than 12 days). This occurs because the critical path switches to activities D and F which are only finished 3.5 days earlier, even though activity C is finished 4 days earlier.

A, 3

C, 2

E, 2.5

B, 2

D, 1.5

F, 3.5

G, 4

NOTE: Enter values from the problem into the yellow highlighted columns to find the solution: ACTIVIT CRITICAL Y DURATION (DAYS) PREDECESSORS ES EF LS LF PATH? A 3 None 0 3 0 3 YES B 2 None 0 2 1 3 C 2 A 3 5 3.5 5.5 D 1.5 A B 3 4.5 3 4.5 YES E 2.5 C D 5 7.5 5.5 8 F 3.5 D 4.5 8 4.5 8 YES G 4 E F 8 12 8 12 YES

Paths: A-C-E-G A-D-E-G A-D-F-G B-D-E-G B-D-F-G

Length: 11.5 11 12 10 11

a.)

A, 1 G, 4

D, 3 B, 2 F, 1.5

E, 2.5

C, 1.5

H, 2

NOTE: Enter values from the problem into the yellow highlighted columns to find the solution: ACTIVIT CRITICAL Y DURATION (DAYS) PREDECESSORS ES EF LS LF PATH? A 1 None 0 1 1 2 B 2 None 0 2 0 2 YES C 1.5 None 0 1.5 1 2.5 D 3 A B 2 5 2 5 YES E 2.5 C 1.5 4 2.5 5 F 1.5 D E 5 6.5 5 6.5 YES G 4 F 6.5 10.5 6.5 10.5 YES H 2 F 6.5 8.5 8.5 10.5 b.) Paths: A-D-F-G A-D-F-H B-D-F-G B-D-F-H C-E-F-G C-E-F-H

Length: 9.5 7.5 10.5 8.5 9.5 7.5

Yes, activity F is on all paths.

c.) The critical activities are B-D-F-G as they are the activities on the critical path. The entire project will take 10.5 days.

d.) No, she should not crash activity E by 1 day as it is not on the critical path; thus the total project time will not be reduced by shortening activity E.

A, 1

A, 1 G, 4

D, 3 B, 2 F, 1.5

C, 1.5

E, 1.5

H, 2

NOTE: Enter values from the problem into the yellow highlighted columns to find the solution: ACTIVIT CRITICAL Y DURATION (DAYS) PREDECESSORS ES EF LS LF PATH? A 1 None 0 1 1 2 B 2 None 0 2 0 2 YES C 1.5 None 0 1.5 1 2.5 D 3 A B 2 5 2 5 YES E 1.5 C 1.5 3 3.5 5 F 1.5 D E 5 6.5 5 6.5 YES G 4 F 6.5 10.5 6.5 10.5 YES H 2 F 6.5 8.5 8.5 10.5

Paths: A-D-F-G A-D-F-H B-D-F-G B-D-F-H C-E-F-G C-E-F-H

Length: 9.5 7.5 10.5 8.5 8.5 6.5

a.) A, 4

B, 3

D, 9

C, 7

G, 6

F, 7

E, 8

I, 4

H, 13

L, 5

J, 12

K, 1

M, 4 N, 5

NOTE: Enter values from the problem into the yellow highlighted columns to find the solution: CRITICAL ACTIVITY DURATION (DAYS) PREDECESSORS ES EF LS LF PATH? A 4 None 0 4 0 4 YES B 3 A 4 7 14 17 C 7 A 4 11 4 11 YES D 9 A 4 13 12 21 E 8 A 4 12 5 13 F 7 B 7 14 17 24 G 6 C 11 17 18 24 H 13 C 11 24 11 24 YES I 4 D E 13 17 21 25 J 12 E 12 24 13 25 K 1 E 12 13 24 25 L 5 F G H 24 29 24 29 YES M 4 I J K 24 28 25 29 N 5 L M 29 34 29 34 YES b.) Paths: A-B-F-L-N A-C-G-L-N A-C-H-L-N A-D-I-M-N A-E-I-M-N A-E-J-M-N A-E-K-M-N

Length: 24 27 34 26 25 33 22

c.) The critical activities are A-C-H-L-N as they make up the critical path. The entire project will take 34 days to complete.

d.) After completing part b and before performing the forward and backward pass, it is known that activity A and N will be part of the critical path because they are activities in every path. They are the start and end activities, so they will always be critical to the project timeline. e.) NOTE: Enter values from the problem into the yellow highlighted columns and use solver (or try values in column N) to find the solution: DURATION (DAYS) CRITICAL Max Days Crash Days to Crash Before After crash PREDECESSORS ES EF LS LF PATH? Crashabl Cost per Crash Cost 4 4 None 0 4 0 4 YES 0 $0 3 3 A 4 7 11 14 0 $0 7 4 A 4 8 4 8 YES 3 $1,000 3 $3,000 9 9 A 4 13 9 18 3 $2,500 0 $0 8 8 A 4 12 4 12 YES 2 $5,000 0 $0 7 7 B 7 14 14 21 0 $0 6 6 C 8 14 15 21 1 $1,000 0 $0 13 13 C 8 21 8 21 YES 3 $3,000 0 $0 4 4 D E 13 17 18 22 0 $0 12 10 E 12 22 12 22 YES 2 $2,000 2 $4,000 1 1 E 12 13 21 22 0 $0 5 5 F G H 21 26 21 26 YES 0 $0 4 4 I J K 22 26 22 26 YES 0 $0 5 5 L M 26 31 26 31 YES 0 $0

ACTIVITY A B C D E F G H I J K L M N

In order to maximize value, management should crash activity C by 3 days and activity J by 2 days. This will reduce the total project completion time by 3 days to 31 days total.

Cost Per Day of Project: Original Days to Complete Project:

$3,500 34

Value of Days Saved: $10,500 Total Cost of Crashed Activities $7,000 Total Value of Crashing Project: $3,500 A, 4

B, 3

F, 7

Total Days Saved: Total Days to Complete Project: D, 9

C, 4

G, 6

E, 8

I, 4

H, 13

L, 5

J, 10

M, 4 N, 5

K, 1

3 31

a.)

A, 4

B, 5

D, 3

C, 7

E, 6

F, 6

G, 8

H, 4

NOTE: Enter values from the problem into the yellow highlighted columns to find the solution: ACTIVIT DURATION CRITICAL Y (WEEKS) PREDECESSORS ES EF LS LF PATH? A 4 None 0 4 8 12 B 5 None 0 5 0 5 YES C 7 B 5 12 5 12 YES D 3 A C 12 15 12 15 YES E 6 B 5 11 17 23 F 6 D 15 21 21 27 G 8 D 15 23 15 23 YES H 4 E G 23 27 23 27 YES b.) Paths: A-D-F A-D-G-H B-C-D-F B-C-D-G-H B-E-H

Length: 13 19 21 27 15

c.) The critical activities are B-C-D-G-H as they are the activities on the critical path. The entire project will take 27 weeks.

d.) ACTIVITY SLACK (WEEKS) A 8 B 0 C 0 D 0 E 12 F 6 G 0 H 0 Activity E has the most slack (12 weeks). The implication is that this activity is very flexible in its start and end dates. e.) Path B-C-D-G-H is the only path greater than 25 weeks, so reducing one or a combination of these activities by two weeks will suffice. Activities A, E, and F are the only ones that should definitely not be crashed. f.) NOTE: Enter values from the problem into the yellow highlighted columns to find the solution: ACTIVIT DURATION CRITICAL Y (WEEKS) PREDECESSORS ES EF LS LF PATH? A 4 None 0 4 1 5 B 5 None 0 5 0 5 YES C 7 A B 5 12 5 12 YES D 3 A C 12 15 12 15 YES E 6 B 5 11 17 23 F 6 D 15 21 21 27 G 8 C D 15 23 15 23 YES H 4 E G 23 27 23 27 YES

There is no impact on the total expected length of the project. Adding activity A as a predecessor to C reduced the slack time available for A but did not put it on the critical path. Adding activity C as a predecessor to G had no effect because C was already a predecessor to D and therefore also a predecessor to G.

a.)

A, 8

E, 6

B, 6

D, 4

C, 3

F, 5

NOTE: Enter values from the problem into the yellow highlighted columns to find the solution: ACTIVIT DURATION CRITICAL Y (WEEKS) PREDECESSORS ES EF LS LF PATH? A 8 None 0 8 1 9 B 6 None 0 6 0 6 YES C 3 None 0 3 7 10 D 4 B 6 10 6 10 YES E 6 A B 8 14 9 15 F 5 C D 10 15 10 15 YES Paths: A-E B-E B-D-F C-F

Length: 14 12 15 8

Activities A, B, and C each start at least one path. Activities E and F each end at least one path. Having multiple starting and ending activities will affect the ES/EF and LS/LF calculations in that they there will be more than one activity to watch for effecting the total project length. b.) The critical activities are B-D-F as they are the activities on the critical path. The entire project will take 15 weeks.

ACTIVIT Y A B C D E F

NOTE: Enter values from the problem into the yellow highlighted columns and use solver (or try values DURATION (WEEKS) Before After crash PREDECESSORS ES EF LS LF 8 7 None 0 7 0 7 6 6 None 0 6 0 6 3 3 None 0 3 5 8 4 2 B 6 8 6 8 6 6 A B 7 13 7 13 5 5 C D 8 13 8 13

c.) The cheapest way to crash the project by 2 weeks is to crash activity A by 1 week and D by 2 weeks. This results in a total crash cost of $7,000. The solution is shown above.

The shortest time in which the project can be completed is 9 weeks. This requires maximum crashing for all activities except for C.

A, 7

E, 6

B, 6

D, 2

C, 3

F, 5

he solution:

and use solver (or try values in column N) to find the solution: CRITICA Weeks Crash Weeks to Crash L PATH? Crashabl Cost per Crash Cost YES 3 $2,000 1 $2,000 YES 1 $4,000 $0 1 $1,000 $0 YES 2 $2,500 2 $5,000 YES 2 $5,000 $0 YES 3 $3,000 $0 $0

$0 $0 $0 $0 $0 $0 $0 Original Weeks to Complete Project:

Total Cost of Crashed Activities

$7,000

Total Weeks Saved: Total Weeks to Complete Project:

2 13

a.) A, 3.5

D, 2

B, 2

C, 4.5

ACTIVIT Y A B C D E F G H

F, 3

E, 2

G, 2

H, 4

NOTE: Enter values from the problem into the yellow highlighted columns and use solver (or try values in column N) to find the solution: CRITICAL Weeks Crash Cost Weeks to DURATION (WEEKS) Before After crash PREDECESSORS ES EF LS LF PATH? Crashable per Week Crash Crash Cost 3.5 3.5 None 0 3.5 0 3.5 YES $0 2 2 None 0 2 1.5 3.5 $0 4.5 4.5 A B 3.5 8 3.5 8 YES $0 2 2 A 3.5 5.5 8 10 $0 2 2 C 8 10 8 10 YES $0 3 2 D E 10 12 10 12 YES 1 $50 1 $50 2 1 F 12 13 12 13 YES 1 $1,500 1 $1,500 4 3 E 10 13 10 13 YES 1 $2,000 1 $2,000

b.) Yes, you should crash the project. If you crash all three activities for a total cost of $3,550 you will save $6000 by decreasing the project by 2 weeks. This results in a net savings of $2,450.

Cost Per Week of Project: Original Weeks to Complete Project:

$3,000 15

Value of Weeks Saved: Total Cost of Crashed Activities Total Value of Crashing Project:

$6,000 $3,550 $2,450

Total Weeks Saved: Total Weeks to Complete Project:

2 13

ACTIVIT Y A B C D E F G H I J

NOTE: Enter values from the problem into the yellow highlighted columns and use solver (or try values in column N) to find the solution: CRITICAL Weeks Crash Cost Weeks to DURATION (WEEKS) ORIGINAL NEW PREDECESSORS ES EF LS LF PATH? Crashable per Week Crash Crash Cost 2 2 None 0 2 1 3 $0 3 3 None 0 3 0 3 YES $0 3 3 A B 3 6 3 6 YES $0 5 5 C 6 11 6 11 YES $0 2 2 D 11 13 11 13 YES $0 3 3 C 6 9 10 13 $0 3 3 E F 13 16 13 16 YES $0 3 2 E 13 15 14 16 1 $2,000 1 $2,000 3 3 E 13 16 13 16 YES $0 2 2 G H I 16 18 16 18 YES $0

a.) No. Although activity H is on the critical path, crashing it will not reduce the total project time.

b.) Activity F can be delayed up to 4 weeks (the slack time) before it will delay the entire project.

Cost Per Week of Project: Original Weeks to Complete Project:

$5,000 18

Value of Weeks Saved: Total Cost of Crashed Activities Total Value of Crashing Project:

$0 $2,000 -$2,000

Total Weeks Saved: Total Weeks to Complete Project:

0 18

Question 1 Important time milestones for this project include the earliest possible start date (September 2020), the project deadline (March 31, 2021), registration deadline (May 15, 2021), as well as the activities listed below.

Activity A B C D E F G

Description Negotiate dates and estimate costs Develop daily schedule of trip Make air transportation arrangements Make local transportation arrangements Select accommodations Finalize loose ends Develop and post online information packet

Duration (Weeks) 1 3 1 1 3 3 1

Question 2 C, 1

A, 1

B, 3

D, 1

F, 3

G, 1

E, 3

NOTE: Enter values from the problem into the yellow highlighted columns to find the solution: ACTIVIT DURATION CRITICAL Y (WEEKS) PREDECESSORS ES EF LS LF PATH? A 1 None 0 1 0 1 YES B 3 A 1 4 1 4 YES C 1 B 4 5 6 7 D 1 B 4 5 6 7 E 3 B 4 7 4 7 YES F 3 C D E 7 10 7 10 YES G 1 F 10 11 10 11 YES In order to post the information packet by March 31, 2021, Robert will need to begin his project 11 weeks earlier. Because the process is mostly linear, only activities C and D have slack time. All other activities are critical as they are on the critical path. Question 3 Robert may want to increase his time estimates to provide extra buffer, especially as this is his first time planning such a trip. There are not likely any pitfalls from starting too early. He may be able to get better estimates of the time it takes for various activities from Professor Wurst, who has been scheduling these trips for 10 years.

Question 1 DFM and DfSC are related in that they are both focused creating a repeatable process for product development and manufacturing. DfSC is focused on creating a repeatable process for product development between the design of a product throughout its lifetime and its supply chain members' resources and capabilities while DFM is creating the product at high quality, low cost with a current process. Question 2 DfSC is a systematic, repeatable process for product development teams and engineers across the life cycle of the product and its supply chain members' resources and capabilities. Parts standardization supports DfSC because it eliminates differences in supplier parts which will help to standardize the processes parts for the teams and engineers. Modular architecture also supports DfSC because it helps define the “chunks” of the process and functions so that it creates a repeatable process for all engineers within the company.

Question 3 These concerns are legitimate in some ways but I believe overall DfSC is a useful approach. It will take more time in the product development process, but it forces communication between all of the different business function groups and that input will create the best possible product. I also think that it does give more power to the supply chain functions, but if shipment costs or manufacturing costs are too high then someone needs to bring that to light. In fact, DfSC is the process of considering supply chain costs and capabilities, and how operations managers can design better product to reduce the overall costs, at the very earliest stages of the design process.

*** Problem Set Key -- Do Not Post or Distribute *** Chapter 3: Process Choice & Layout Decisions in Manufacturing & Services Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd Edition) DIRECTIONS To generate the key, put in the 4-digit number used when printing off the original assignment. Name: *** KEY *** 4-digit number: 7500 75 Problem 1

Max Products is setting up an assembly line to produce radio dog collars. The line will run 12 hours a day, and will need to produce 400 collars a day. The various tasks, along with their required times and immediate predecessors, are shown below.

Task A B C D E F G H I J K L M Total Problem 1

Time Immediate (minutes) Predecessor(s) 70 none 32 none 49 none 19 A, B 38 B, C 68 D 14 D 22 D 11 E 45 G, H, I 10 F, G, H 22 K, J 24 K, J 424

seconds

In the space below, calculate the takt time and the minimum number of workstations for the line. Show your work. Takt time = Available production time Required output rate

(12*60*60)/ 400 = 108 seconds

Minimum number of workstations = = which rounds up to

(Total task time) / (Takt time) 3.93 4 workstations

*** KEY *** Problem 2

Suppose that management ignores the takt time and minimum workstation calculations in Problem 1, and decides to set up four workstations, as follows: Workstation 1: Workstation 2: Workstation 3: Workstation 4:

Activities A and C Activities B, D, E, G and H Activities F, I and K J, L and M

In the space below, calculate the cycle time for this line, as well as the idle time and percent idle time.

Workstation 1 2 3 4 Total

Total task time 119 125 89 91 424

Cycle time = maximum total task time of all workstations =

125

Idle time = (No. of workstations)*(Cycle time) - Total task time) = 76 seconds % idle time = 100% * (Idle time) / (Total task time) = 17.92%

*** Problem Set Key -- Do Not Post or Distribute *** Chapter 4: Business Processes Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd Edition) DIRECTIONS 1. Put your name and the four-digit number provided by your instructor in the space below,and hit enter. This will customize the assignment for you. 2. Print out the entire workbook and put your answers in the space provided. Name: *** KEY *** 4-digit number: 1500 20 Consider the output and machine and machine hour figures shown below. Month 1 2 3 4 5 6 7 8

Problem 1

Output 60 54 66 63 57 66 51 64

Mach. Hrs. 1200 1100 1300 1300 1150 1350 1100 1100

In the space below, calculate the machine productivity for each month, as well as the average machine productivity for all 8 months. Do any of the months seem "unusual" to you? Explain.

Productivity = Outputs / Inputs Month

Ave:

Productivity 1 0.050 units per machine hour 2 0.049 3 0.051 4 0.048 This last month seems 5 0.050 significantly higher than 6 0.049 the rest. We might investi7 0.046 gate to determine why this 8 0.058 was the case. 0.050

*** KEY *** In 2013, Gibison's Auto Repair invested in a computer diagnostic machine that reads codes on a car's computer, thereby shortening the time it takes to determine what is wrong with a car. Consider the figures below: Year 2010 2011 2012 2013 2014 2015 Problem 2

Year 2010 2011 2012 2013 2014 2015 Problem 3

Year 2000 2001 2002 2003 2004 2005

Sales ($000s) Labor costs ($000s) Machine costs ($000s) $2,468 $987 $0 $2,838 $1,192 $0 $3,085 $1,172 $0 $3,702 $1,074 $150 $4,072 $1,140 $150 $4,319 $1,166 $150 In the space below, calculate the labor productivity for each of the six years. How much has labor productivity improved since the diagnostic machine was brought in?

Labor prod. 2.50 2.38 2.63 3.45 3.57 3.70

For 2000-2002, each labor dollar generated in sales, on average.

$2.50

For 2003-2005, each labor dollar generated in sales, on average.

$3.57

In the space below, calculate the multi-factor productivity score for each year, where the "input" is the total amount spent on labor and the diagnostic machine. Next, calculate the average multi-factor productivity score for years 2000 - 2002, and years 2003 - 2005. According to the results, was it worthwhile for Gibson to invest in the diagnostic machine? Why or why not? Multi-factor productivity $2.50 $2.38 $2.63 $3.02 $3.16 $3.28

For 2000-2002,each dollar spent on labor and diag. machine generated sales of

$2.50

For 2000-2003,each dollar spent on labor and diag. machine generated sales of

$3.15

According to these results, the cost of the diagnostic machine was more

than offset by the increased productivity of labor.

*** KEY *** Hyattsville Healthcare has determined that the standard time to process a customer's insurance claim is 3 minutes. Elizabeth Arnold, supervisor, has recorded the following results for two of her employees (each works an 8-hour day):

Day 1 2 3 4

Total claims processed: Myra Jane 192 128 176 156 208 132 160 154

Problem 4 In the space below, calculate the efficiency for Myra, and then for Jane. Interpet the results. What other factors might we want to consider, besides efficiency, when evaluating the performance of Myra and Jane? Four 8-hour days equals 32 hours, or 1920 Based on the standard, an employee should process In this time, Myra processed In this time, Jane processed

736 570

minutes 640.00 forms in this time

forms, for an efficiency of forms, for an efficiency of

115.00% 89.06%

Even though Myra appears to be more efficient than Jane, we might want to look at the difficulty of the forms processed, as well as the quality levels (ie, how many forms are processed erroneously) before making any final judgements.

Problem 5 Barbers at the ManMur Barber Shop take, on average, 10 minutes to cut a customer's hair. The average wait time is 5 minutes on a typical day, but can stretch as long as minutes on a busy day. In the space below, calculate the percent value-added time for a) a typical day, and b) a busy day.

On a typical day, the percent-value-added time is On a busy day, it drops down to

33.33%

66.67%

a customer's 20

*** Problem Set Key: Do Not Post or Distribute *** Chapter 5: Managing Quality Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd Edition) DIRECTIONS To generate the key, put the same 4-digit number in the space below that was used in printing out the original assignment. Name: *** KEY *** 4-digit number: 2000 20 Buff n' Tuff Products produces bottles of free-range steroids. The stated size of each bottle is 20 ounces. In order to assess the accuracy of the bottle filling process, Buff n' Tuff took 10 samples of 6 observations each when the process was working as expected. The table below shows the weight (in ounces) for each sample bottle. *************** Observations ****************** Sample 1 2 3 4 5 6 1 19.52 20.15 20.45 19.76 20.32 20.49 2 20.26 20.45 19.99 20.56 19.68 20.29 3 20.52 19.85 19.43 19.61 19.5 19.76 4 20.07 20.04 20.31 20.37 19.52 19.86 5 20.15 19.4 20.03 20.34 20.5 20.17 6 19.98 19.87 19.21 20.14 20.5 20.32 7 20.24 20.32 19.81 19.58 19.59 20.68 8 20.21 20.08 19.89 20.38 20.2 20.04 9 19.85 19.86 20.7 20.84 20.46 20.01 10 20.07 19.8 19.89 19.98 20.65 20.16

*** KEY *** Problem 1

In the space below, set up the X and R charts for the Buff n' Tuff filling process, Show how you calculated the upper and lower control limits for each chart. *************** Observations ****************** 1 2 3 4 5 6 X-bar 19.52 20.15 20.45 19.76 20.32 20.49 20.12 20.26 20.45 19.99 20.56 19.68 20.29 20.21 20.52 19.85 19.43 19.61 19.5 19.76 19.78 20.07 20.04 20.31 20.37 19.52 19.86 20.03 20.15 19.4 20.03 20.34 20.5 20.17 20.10 19.98 19.87 19.21 20.14 20.5 20.32 20.00 20.24 20.32 19.81 19.58 19.59 20.68 20.04 20.21 20.08 19.89 20.38 20.2 20.04 20.13 19.85 19.86 20.7 20.84 20.46 20.01 20.29 20.07 19.8 19.89 19.98 20.65 20.16 20.09 Grand mean: 20.08 R-bar: For the X-bar chart, the center value is the grand mean For the R-bar chart, the center value is R-Bar The control limits for a sample of size 6 are as follows: UCLX-bar =Grand Mean + A3*R-bar = 20.54 LCLX-bar =Grand Mean - A3*R-bar = 19.62 UCLR-bar = D3*R-bar = 0.00 LCLR-bar = D4*R-bar = 1.92 Sample 1 2 3 4 5 6 7 8 9 10

Problem 2

The standard deviation of the individual observations equals: 0.364 The upper and lower tolerance limits are 21.4 and 18.6 In the space below, calculate the process capability index for the process. Also, what would the standard deviation have to be in order to support six sigma quality levels? Show all work. Our estimate of m is the grand mean from Prob. 1:

20.08

The process capability index = minimum [(m - LTL )/ 3s , (UTL - m) / 3s ) = =

min ( 0.16044 , 0.16044

0.17929 )

For six sigma quality, (UTL - LTL) / 12s would need to be 1 or greater

Therefore, s would have to be

0.23333 or lower

*** KEY ***

R 0.97 0.88 1.09 0.85 1.10 1.29 1.10 0.49 0.99 0.85 0.96

Duff Gardens Amusement Park likes to track customer satisfaction levels. Over a course of 15 days, management asked a random sample of guests whether they were happy or unhappy with their overall experience. The sample results are shown below:

Sample 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Problem 3

No. of Sample unhappy Size guests 30 2 30 1 30 1 30 1 30 1 30 1 30 1 30 2 30 2 30 2 30 2 30 1 30 1 30 2 30 2

In the space below, set up the p chart required to track the proportion of dissatisfied guests. Round your p value to three decimal points (ex. - 0.067 = 6.7%) ALSO, answer the following question in one or two sentences: What should Duff Gardens do if a future sample falls above the UCL?

Sample 1 2 3 4 5 6 7 8

No. of Sample unhappy Size guests 30 2 30 1 30 1 30 1 30 1 30 1 30 1 30 2

p 0.067 0.033 0.033 0.033 0.033 0.033 0.033 0.067

Sp =

0.039

UCLp = p-bar + 3*Sp = LCLp = p-bar - 3*Sp=

If a future sample falls above the UCL, it impl an unusually large number of customers were dissatisfied. While Duff Gardens wouldn't

9 10 11 12 13 14 15

30 30 30 30 30 30 30

2 2 2 1 1 2 2 p-bar:

0.067 0.067 0.067 0.033 0.033 0.067 0.067 0.049

want to close the park, they *should* immedia start diagnosing why they are having such unusually high dissatisfaction levels.

*** KEY ***

0.167 0

lls above the UCL, it implies umber of customers were Duff Gardens wouldn't

*** Problem Set Key -Do Not Post or Distribute *** Chapter 6: Managing Capacity Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd DIRECTIONS

To generate the key, put in the same 4-digit number used to generate the original homework problem. The correct answers will be generated automatically.

Name: *** KEY *** 4-digit number: 3456 40 To earn money while he is in school, Scott has decided to clean carpets on the side. Scott can either rent, lease, or buy the equipment. The costs associated with each of the three capacity options are shown below:

Option Rent Lease Buy

Yearly fixed cost $1,050.00 $3,150.00 $7,350.00

Variable cost per job $210.00 $189.00 $147.00

In addition, Scott estimates that the revenue for each job will be, on average, Finally, Scott has identified three possible demand scenarios: Scenario Demand Probability Low 40 15% Moderate 90 70% High 120 15%

Problem 1

Calculate the break-even point for each capacity option. BEP = (Fixed cost) / (Revenue per job - variable cost per job) BEP(Rent) = BEP(Lease) = BEP(Buy) =

50.00 jobs 75.00 jobs 87.50 jobs

$231.00

rth & Handfield, 3rd Edition)

*** KEY ***

Problem 2 Draw a decision tree showing all possible outcomes facing Scott. Calculate the profit (revenues - total costs) for each possible outcome and include these on your tree. What is the expected monetary value for each of the three capacity options? Rent EV =

R Lease EV = e n t Le ase B u Buy EV = y

$777.00

$504.00

($42.00)

LOW DEMAND

($210.00)

MOD. DEMAND

$840.00

HIGH DEMAND

$1,470.00

LOW DEMAND

($1,470.00)

MOD. DEMAND

$630.00

HIGH DEMAND

$1,890.00

LOW DEMAND

($3,990.00)

MOD. DEMAND

$210.00

HIGH DEMAND

$2,730.00

*** Problem Set Key: Do Not Post or Distribute *** Chapter 6: Managing Capacity Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd DIRECTIONS To generate the key, put in the same 4-digit number used to generate the homework set. Name: *** KEY *** 4-digit number: 4531

Problem 1

You are the new CEO of CompuZip, a retailer that sells PCs for $2500. You must decide whether to assemble the PCs in-house, or have a Mexican company do it. The fixed and variable costs for each option are shown below: Fixed Cost Assemble in-house Mexican assembler

1a. 1b. 1c.

Variable Cost 55000 267 0 103

Suppose the PCs sell for $2500. What is the break-even volume point for doing it in-house? At what volume level do the two capacity options have identical costs? Suppose the expected demand for PCs is 3000. Which capacity option would you prefer from a cost perspective? BEP (In-house) =

24.63 PCs

The two capacity options have identical costs at Total in-house cost for 3000: Total Mexican cost at 3000:

Problem 2

2b. 2c.

$856,000 $309,000 *** Low cost option ***

After graduating you take a job with a local software development firm. The time for your first and second projects are shown below. Time for first project Time for second project

2a.

-335.37 PCs

110 hours 88 hours

Based on just these two sample points, what is your estimated learning rate? (Round your answer to the nearest 5%, such as 95%, 90%, 85%, etc.) According to 2a, how many hours should it take you to complete the next 5 projects? How long should it take to complete the 10th project? Estimated learning curve:

80.00%

The "next 5"projects means projects 2 through 7:

Using Table 8.6, the time for Projects 2 - 7:

333.74 hours

And the time for the 10th project:

52.47 hours

*** KEY *** Problem 3 Will Stallard runs a landscaping firm. Each year, Will contracts for labor and equipment hours from a local construction company. The construction company has given Will three different capacity options, shown below: Capacity Options High capacity Medium capacity Low capacity

Labor hrs Eq. hrs. 20400 13600 15300 10200 10200 6800

Cost per labor hour: Cost per equip. hour:

$10 per hour $20 per hour

Once Will has chosen a capacity option, he cannot change it later. In addition, the cost for each capacity option is fixed. That is, Will must pay for all labor and equipment hours he contracted for, even if he doesn't need it all. Will also has information concerning the amount of revenue, labor and equipment hours needed for the "typical" landscaping job: Job Revenue: Labor hours per job: Equip. hours per job:

$2,000 per job 30 hours 20 hours

Will has identified three possible demand levels. These demand levels, with their associated probabilities, are shown below: Demand Level High demand Medium demand Low demand

3a. 3b.

3c.

# Jobs 680 453 272

Probability 40% 20% 40%

Determine the total cost of each capacity option. What are the nine possible outcomes Will is facing? (Hint: One is "Will subcontracts for low capacity and demand turns out to be low") What is the profit (Revenue - fixed costs) associated with each outcome? Using the information from 2b, calculate the expected monetary value (EMV) for each of the three capacity options. Show your work. Which option would Will prefer if he wanted to maximize EMV?

High capacity: Medium capacity Low capacity

Total cost $476,000 $357,000 $238,000

Max jobs, labor. 680 510 340

Max jobs, equip 680 510 340

Effective Capacity 680 510 340

Profit for each possible outcome & EMV for each capacity alternative: High cap / high demand: High cap / med demand: High cap / low demand: Med cap / high demand:

$884,000 $430,000 $68,000 $663,000

EMV =

$466,800 ***Highest EMV***

Med cap / med demand: Med cap / low demand: Low cap / high demand: Low cap / med demand: Low cap / low demand:

$549,000 $187,000 $442,000 $442,000 $306,000

EMV =

$449,800

EMV =

$387,600

Chapter 7: Supply Management Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd Ed.) DIRECTIONS 1. Put your name and the four-digit number provided by your instructor in the space below,and hit enter. This will customize the assignment for you. 2. Print out the entire workbook and put your answers in the space provided. Name: Jane Student 4-digit number: 1500 15

Zeccardi Sporting Goods produces gear used by baseball and softball players. The company is thinking about outsourcing the production of a particular product to a Costa Rican manufacturer. The Costa Rican manufacturer has offered to produce the products at a cost of $30 each , based on an annual volume of 67,500 units. Zeccardi management has developed the following figures: Current manufacturing operations

Costa Rican manufacturer

Fixed Costs:

$150,000 per year

Cost per product:

$23 per unit $11 per unit

Other costs: Admin costs = Inspect costs = Shipping / pack =

Variable Costs: Labor Material

$30

$20,000 per year $15,000 per year $1.50 per unit

In addition to cost, Zeccardi management has identified three other dimensions to consider: conformance quality, on-time delivery, and product range flexibility. The importance weights for these three dimensions are 0.4, 0.3, and 0.2, respectively. Finally, purchasing experts at Zeccardi have rated the performance of current manufacturing and the Cost Rican manufacturer with regard to these three dimensions. Their ratings (1 = "poor" to 5 = "excellent") are as follows:

Dimension Quality On-time Del. Flexibility

******* Performance Rating ********* Current mfg. Costa Rican Mfr. 5 3 3 2 2 5

Jane Student Problem 1 In the space below, calculate the total costs of a) continuing to manufacture the product in-house, and b) outsourcing manufacturing to the Costa Rican manufacturer.

Annual volume =

67,500 at a price of

$30.00 per unit

Cost of curr. mfg. ops = (Variable unit labor cost + variable unit material cost) * annual volume + fixed costs = $2,295,000 + $150,000 = $2,445,000 Cost of outsourcing = (Cost per unit + shipping cost per unit)*annual volume + other costs = $2,126,250 + $35,000 = $2,161,250

Problem 2 Calculate the overall preference score for each of the two options. Compare these results with those in Problem 1. How do you account for the discrepency? How should Zeccardi weigh the various results?

******* Performance Rating ********* Dimension Weight Current mfg. Wt. Score Costa Rica Wt. Score Quality 0.4 5 2 3 1.2 On-time Del. 0.3 3 0.9 2 0.6 Flexibility 0.2 2 0.4 5 1 Overall preference scores:

3.3

2.8

The option with the highest score here is considered better overall with regard to quality, on-time delivery and flexibility. This result may differ from Problem 1 because Problem 1 is concerned with *costs*, not these other factors.

*** Problem Set Key -- Do Not Post or Distribute *** Chapter 8: Logistics Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd Ed.) DIRECTIONS 1. Put your name and the four-digit number provided by your instructor in the space below,and hit enter. This will customize the assignment for you. 2. Print out the entire workbook and put your answers in the space provided. Name: *** KEY *** 4-digit number: 5000 50 Every week, Markham Ltd makes shipments to 40 customers in Chicago. Each customers order weighs 5000 lbs. The cost of direct truckload shipment from Salt Lake City (where Markham is located) to Chicago costs $2,200 Given the density of the shipments, each truck could carry a maximum of 20,000 lbs. Problem 1

What would it cost Markham to make direct, single order shipments to all of its customers each week? What would the utilization levels for the trucks look like? Put your answer in the space below.

Direct shipments to each customer would cost: The utilization level for each truck would be:

Problem 2

$88,000 25.00%

Now suppose a Chicago-based warehousing firm has agreed to run a break-bulk operation for $22 per hundred-weight and $90 per local delivery. How many trucks would be required? What would the total trucking, warehousing, and local delivery costs be? Put your answers in the space below. Number of truckloads needed = (Weight of all shipments) / Truck maximum = 10.00 trucks, or 10 trucks (rounding up)

Trucking costs: $22,000 (No. of trucks X $2,200 per truck) Warehousing cost: $44,000 ($22 X Total shipment weight / 100) Local del. cost: $3,600 ($90 X Total number of customers) TOTAL COSTS: $69,600

*** KEY *** Whole Foods is a specialized grocery store that caters to customers wanting organically-grown foods, free-range meats, and products with low environmental impact. Whole Foods is trying to determine where to locate a new grocery store in the town of Chapel Hill. The grocery store is expected to serve five neighborhoods, shown below. The (X,Y) map coordinates & number of homes are shown below: Neighborhood Glenview Place Townley Circle Springdale Jamestown Emerson Bridge Problem 3

X coord. Y coord. 6 2 6.5 5 2 2.5 3 4 4.5 3.5

Homes 90 60 55 80 50

Calculate the weighted center of gravity for the new grocery store, based on the information above. What other factors might Whole Foods consider before making a final decision?

Neighborhood Glenview Place Townley Circle Springdale Jamestown Emerson Bridge

*** Coordinates *** X coord. Y coord. Homes X*homes Y*homes 6 2 90 540 180 6.5 5 60 390 300 2 2.5 55 110 137.5 3 4 80 240 320 4.5 3.5 50 225 175 Total: 335 Weighted Average; 4.49 3.32

Other factors to consider are zoning laws, property prices, and even the demographics of the neighborhoods -- is there a market for the specialized products and services?

Chapter 9: Forecasting Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd DIRECTIONS

Enter the instructor-provided 4-digit number to generate the homework key.

Name: *** KEY *** 4-digit number: 4545

Problem 1

Develop a single exponential smoothing forecast for Periods 1 through 9, using the data below. Each time you develop a forecast, round your answer off to a whole number (ex. - 2012.6 = 2013). Use a smoothing constant value of 0.3. Actual Week

Demand

Forecast

4545

4500

4091

4514

4318

4387

4636

4366

4181

4447

4863

4367

4363

4516

4727

4470

4547

*** KEY ***

Problem 2

Use regression analysis to develop a time series forecasting model for the data below, and develop seasonal indices for each month. Use your regression model to forecast develop forecasts for January and February of 2016. Y Month Demand January, 2014 636 February 748 March 611 April 538 May 468 June 343 July 283 August 328 September 454 October 522 November 649 December 645 January, 2015 685 February 565 March 458 April 401 May 346 June 252 July 204 August 237 September 324 October 369 November 427 December 446 Sum: 10939

Problem 3

X 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 300

X*Y 636 1496 1833 2152 2340 2058 1981 2624 4086 5220 7139 7740 8905 7910 6870 6416 5882 4536 3876 4740 6804 8118 9821 10704 123887

X^2 1 4 9 16 25 36 49 64 81 100 121 144 169 196 225 256 289 324 361 400 441 484 529 576 4900

y = a + b(Period) Slope coefficent (b) =

-11.1743

Intercept term (a) =

595.471

Forecasts: Jan. 2016 (Period 25): Feb. 2016 (Period 26):

316.11 304.94

Calculate the mean forecast error and mean absolute deviation for the two forecast models shown below. Which model has the least bias? Which model has the lowest overall forecast errors?

Period

Actual Demand

Forecast Model 1

1 2 3 4 5 6 7 8 9 10

11000 9500 10500 10200 8800 8300 7900 8500 9700 10000

11000 11000 11000 11000 8800 8800 8800 8800 10500 10500 Mean:

Forecast Model 2 FE 0 -1500 -500 -800 0 -500 -900 -300 -800 -500 -580

AD 0 1500 500 800 0 500 900 300 800 500 580

10335 10335 10335 9100 9100 9100 8700 8700 8700 8700

FE 665 -835 165 1100 -300 -800 -800 -200 1000 1300 129.5

The model with the MFE closest to zero has the least bias. The model with the smallest MAD has the lowest overall forecast errors.

*** KEY ***

orecast errors?

AD 665 835 165 1100 300 800 800 200 1000 1300 716.5

*** Problem Set Key - Do Not Post or Distribute *** Chapter 9: Forecasting Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd Ed.) DIRECTIONS

To generate the homework key, input the same 4-digit number used to create the original homework assignment. The correct answers will automatically be generated. Name: *** KEY *** 4-digit number: 2000 20

ChesterBoz makes high-end boogie boards, with most sales coming from the U.S. The table and graph below show the demand for the last two years. Period June, 2014 July August September October November December Jan. 2015 February March April May June July August September Octoer November December Jan. 2016 February March April May

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Demand 3880 3560 3320 3430 3030 3010 3170 3040 3360 3600 4580 4720 4620 4140 4150 3810 3230 2960 3200 3360 3590 3930 5710 5470

6000 5000 4000 3000 2000 1000 0 1 3 5 7 9 11 13 15 17 19 21 23

Period Demand

Problem 1

Develop 2-period & 3-period moving average models forecast for Periods 19 through 24. Calculate MFE & MAD for Periods 19 through 24 for the resulting forecast model. Which model has the least bias? Which model has relatively smaller errors? Show all your work.

2-period forecast September Octoer November December Jan. 2006 February March April May

16 17 18 19 20 21 22 23 24

3810 3230 2960 3200 3360 3590 3930 5710 5470

3095.00 3080.00 3280.00 3475.00 3760.00 4820.00 Means:

3-period forecast September Octoer November December Jan. 2006 February March April May

Problem 2

16 17 18 19 20 21 22 23 24

3810 3230 2960 3200 3360 3590 3930 5710 5470

3333.33 3130.00 3173.33 3383.33 3626.67 4410.00 Means:

Forecast Absolute error deviation

105.00 280.00 310.00 455.00 1950.00 650.00 625.00

The model with MFE closest to zero has the least bias.

The model with the smallest MAD has the smallest errors, on average.

Forecast Absolute error deviation

-133.33 230.00 416.67 546.67 2083.33 1060.00 700.56

133.33 230.00 416.67 546.67 2083.33 1060.00 745.00

In either case, neither model does a good job picking up on the overall upward trend in the data.

Develop an SESM forecasting model with a = 0.35 for Periods 19 through 24. Calculate MAD and MFE for Periods 19 through 24 (n =6) for the resulting forecast model. Assume your forecast for period 18 was 2900

November December Jan. 2006 February March April May

18 19 20 21 22 23 24

Forecast Absolute SESM forecast error deviation 2960 2900 3200 2921.00 279.00 279.00 3360 3018.65 341.35 341.35 3590 3138.12 451.88 451.88 3930 3296.28 633.72 633.72 5710 3518.08 2191.92 2191.92 5470 4285.25 1184.75 1184.75

Once again, the time series model fails to pick up on the upward trend in the data.

Means:

847.10

*** KEY ***

9 through 24.

Show all your work.

The model with MFE closest to zero has the least bias. The model with the smallest MAD has the smallest errors, on average.

In either case, neither model does a good job picking up on the overall upward trend in the data.

gh 24. Calculate MAD

Once again, the time series model fails to pick up on the upward trend in the

Problem 3

Use regression analysis to develop a forecast model using the two years of data. Develop seasonal indices for the months of June and January only. Use your model to forecast demand for June, 2016 & January, 2017. X Period

June, 2004 July August September October November December Jan. 2005 February March April May June July August September Octoer November December Jan. 2006 February March April May SUMS:

Y Unadj. Demand / Demand X*Y X^2 regress. Forecast 1 3880 3880 1 3249.60 1.19 2 3560 7120 4 3296.27 1.08 3 3320 9960 9 3342.93 0.99 4 3430 13720 16 3389.60 1.01 5 3030 15150 25 3436.26 0.88 6 3010 18060 36 3482.93 0.86 7 3170 22190 49 3529.59 0.90 8 3040 24320 64 3576.26 0.85 9 3360 30240 81 3622.92 0.93 10 3600 36000 100 3669.59 0.98 11 4580 50380 121 3716.25 1.23 12 4720 56640 144 3762.92 1.25 13 4620 60060 169 3809.58 1.21 14 4140 57960 196 3856.25 1.07 15 4150 62250 225 3902.91 1.06 16 3810 60960 256 3949.58 0.96 17 3230 54910 289 3996.24 0.81 18 2960 53280 324 4042.91 0.73 19 3200 60800 361 4089.57 0.78 20 3360 67200 400 4136.24 0.81 21 3590 75390 441 4182.90 0.86 22 3930 86460 484 4229.57 0.93 23 5710 131330 529 4276.23 1.34 24 5470 131280 576 4322.90 1.27 300 90870 1189540 4900

Unadjusted regression model: y = a + bX a= 3202.93 b= 46.67

Seasonal indices, calculated as average of demand/foreca ratios for past years: 1.20 Adjusted forecast for 6/07 (Period 37):

0.83 Adjusted forecast for 1/07 (Period 32):

*** KEY ***

a. Develop seasonal indices for r June, 2016 & January, 2017.

Seasonal indices, calculated as average of demand/forecast ratios for past years: for June Adjusted forecast for 6/07 (Period 37):

5932.03

for January Adjusted forecast for 1/07 (Period 32):

3903.46

*** Problem Set Key -- Do Not Post or Distribute *** Chapter 10: Sales & Operations Planning (Aggregate Planning) Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd Ed.) DIRECTIONS

To generate the key, plug in the same 4-digit number used to create the original homework set. Name: *** KEY *** 4-digit number: 9999

Pennsylvania Replicas makes two types of traditional Shaker tables: The Simplicity and the Work The two lines are made in the same facility using the same labor and equipment. In addition, we k

* Each Simplicity and Workman table requires, on average, about 3.2 hours of labor. * Each employee works 160 hours per month, and there is no effective limit on the number of em * The cost of hiring or firing an employee is $900 * The monthly holding cost for a table is $9.50 * For planning purposes, the beginning and ending workforce is 35 * At the beginning of the planning period, there are 0 units in inventory

Month November December January February March April May June July August

Problem 1

Simplicity Workman Demand Demand 750 6750 875 7875 1000 9000 1000 9000 1250 11250 1250 11250 1500 13500 1500 13500 1625 14625 1750 15750

7500 8750 10000 10000 12500 12500 15000 15000 16250 17500

750.00 875.00 1000.00 1000.00 1250.00 1250.00 1500.00 1500.00 1625.00 1750.00 1250.00

0.6 . 0.7 0.8 0.8 1 1 1.2 1.2 1.3 1.4

0.8

Develop a level S&OP for November - August. Show aggregated monthly production, workforce and ending inventory levels; monthly hirings and firings; and total hiring, firing, and inventory costs. To keep it simple, assume you can have fractional units in inventory, and that you can hire / fire fractional numbers of employees (ex. - 25.5 employees)

andfield, 3rd Ed.)

The Simplicity and the Workman . d equipment. In addition, we know that:

3.2 hours of labor. ive limit on the number of employees

tory levels;

employees

*** KEY ***

Problem 1 Develop a level S&OP for November - August. Show aggregated monthly production, workforce and ending inventory levels; monthly hirings and firings; and total hiring, firing, and inventory costs. To keep it simple, assume you can have fractional units in inventory, and that you can hire / fire fractional numbers of employees (ex. - 25.5 employees) Month November December January February March April May June July August

Simplicity Workman Demand Demand 750 875 1000 1000 1250 1250 1500 1500 1625 1750

6750 7875 9000 9000 11250 11250 13500 13500 14625 15750

Inventory cost: Hiring & Firing cost: Total:

Total Demand

Total hours

Workers needed

7500 8750 10000 10000 12500 12500 15000 15000 16250 17500

24000 28000 32000 32000 40000 40000 48000 48000 52000 56000 Ave:

150 175 200 200 250 250 300 300 325 350 250

Actual workers 35 250 250 250 250 250 250 250 250 250 250 35 Totals:

Hires

Fires

215 0 0 0 0 0 0 0 0 0 0 215

0 0 0 0 0 0 0 0 0 0 215 215

Hires

Fires

115 25 25 0 50 0 50 0 25 25 0 315

0 0 0 0 0 0 0 0 0 0 315 315

$866,875 $387,000 $1,253,875

Problem 2 Develop a chase S&OP for November - August. Follow the same instructions as in Problem 1. Month November December January February March April May June July August

Simplicity Workman Demand Demand 750 875 1000 1000 1250 1250 1500 1500 1625 1750

6750 7875 9000 9000 11250 11250 13500 13500 14625 15750

Inventory cost: Hiring & Firing cost: Total:

Total Demand

Total hours

Workers needed

7500 8750 10000 10000 12500 12500 15000 15000 16250 17500

24000 28000 32000 32000 40000 40000 48000 48000 52000 56000 Ave:

150 175 200 200 250 250 300 300 325 350 250

$0 $567,000 $567,000

Actual workers 35 150 175 200 200 250 250 300 300 325 350 35 Totals:

Ending Inventory 0 5000 8750 11250 13750 13750 13750 11250 8750 5000 0 91250

Ending Inventory 0 0 0 0 0 0 0 0 0 0 0 0

*** Problem Set Key -- Do Not Post or Distribute *** Chapter 11: Managing Inventory Throughout the Supply Chain Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd DIRECTIONS

To generate the key, put in the space below the same 4-digit number used to generate the original homework. Name: *** KEY *** 4-digit number: 1000 Northcutt Bikes purchases two types of wheels for their roadracing bikes: a regular version and a deluxe version. The table below has demand information for the past year for each style of wheel, as well as combined figures.

Month January February March April May June July August September October November December Ave. Monthly Demand Std. Dev., Monthly Demand

Problem 1

REGULAR Wheels 208 153 238 296 292 322 102 211 286 163 186 129

DELUXE Wheels 481 316 553 648 228 527 605 510 538 590 657 582

Combined Demand 689 469 791 944 520 849 707 721 824 753 843 711

215.5 72.1

519.6 122.8

735.1 129.2

1849.884 1361.158 2122.129 2638.237 2599.175 2866.567 908.2062 1882.909 2547.511 1456.65 1654.898 1154.784

Other important information: 1070.467 703.2119 Yearly holding cost 1230.538 Ordering cost 1441.763 Service level 507.9288 Leadtime 1173.325 1344.477 Item costs 1133.85 Deluxe Wheels 1195.676 Regular Wheels 1311.482 1462.026 1295.332

Calculate the EOQ for each wheel separately. Show your work in the space below.

Regular wheels: Estimated annual demand = Annual holding cost / unit = EOQ = 384.41

2586 = D in EOQ formula $7.0 = H in EOQ formujla

Deluxe wheels: Estimated annual demand = Annual holding cost / unit = EOQ = 558.35

6235 = D in EOQ formula $8.0 = H in EOQ formujla

Problem 2

Calculate the ROP separately for each wheel. Show your work in the space below.

Since no standard deviation for lead time is given, we must assume that lead time is contan (ie, no variance). Furthermore, for a service level of 95%, z = 1.65. Regular wheels ROP:

191.83 units

Safety stock =

Deluxe wheels ROP:

403.12 units

Safety stock =

arth & Handfield, 3rd Ed.)

and information for the past year

Other important information: 20% of item cost $200 per order 95% 0.5 months

$40 each $35 each

the space below.

ssume that lead time is contant

84.08 units 143.32 units

*** KEY *** Problem 3

For each wheel, calculate the total yearly holding and ordering cost, as well as total item cost. (Note: Assume average inventory level = Q/2 + Safety Stock) What are the combined costs for the two seats?

For regular wheels, EOQ =

384.41

Annual holding cost = Annual ordering cost = Annual item cost = Total:

$1,933.99 $1,345.44 $90,510.00 $93,789.42

For deluxe wheels, EOQ =

558.35

Annual holding cost = Annual ordering cost = Annual item cost = Total:

$3,379.97 $2,233.38 $249,400.00 $255,013.35

Grand total (both):

Problem 4 Advanced Question

$348,802.78

Jan is thinking about using the deluxe wheels on all bikes, yet still charge her customers the same price. Repeat Problems 1-3, except this time assume that all demand will be met by the deluxe wheels. Considering ordering, holding and item costs, will it be cheaper or more expensive to use deluxe wheels on Show your work.

New D for EOQ is combined demand: S would still be $200 H would be holding cost / unit for deluxe: EOQ = SS =

8821 $200.00 $8.00

664.12 units 150.76 units

(using std dev of combined demand

Total holding cost for the year, based on the EOQ: Total ording cost for the year, based on the EOQ: Total item costs for the year (combined demand):

$3,862.58 $2,656.46 $352,840

Grand total:

$359,359.05

*** Problem Key - Do Not Post or Distribute *** Chapter 12: Managing Production Across the Supply Chain Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd Ed.) DIRECTIONS

To generate the key, input the same 4-digit number used to create the original homework set. The correct answers will be generaed automatically. Name: *** KEY *** 4-digit #: 9000

Baxter Pharmaceuticals has developed a new drug to help students keep awake while studying for exams. The bill-of-material (BOM) for a single full bottle of FinalZing is shown below. FinalZing * 1 week LT * No min order quantity

Bottle * 3 week LT * Min order = 9,000

Problem 1

Cap * 1 week LT * Min order = 50,000

Comp. W

Chem. X * 4 oz * 1 week LT * no minimum

Chem. Y * 2 oz * 2 week LT * 80,000 oz min

Below is the master production schedule for cases of FinalZing. Each case holds 20 bottles of FinalZing. Complete the projected on-hand inventory and available-to-promise calculations for the record. Beginning Inventory: 1 Forecast Orders Booked Projected On-hand Master Schedule Available-to-promise

300 327 1240 1290 429

277 2

WEEK 4

3 330 290 910 0

330 264 580 0

5 330 257 250 0

6 360 216 610 720 112

360 392 218 0

ld, 3rd Ed.)

* 6 oz * 1 week LT * 10,000 oz min

* 2 week LT * 80,000 oz min

8 360 198 638 780 456

420 126 218 0

Problem 2

Complete the MRP records shown below, using the BOM information on the first page. Be sure to consider all lead times, minimum order sizes, beginning inventories and scheduled receipts when developing your answers. NOTE THE FOLLOWING: The MRP records below expresses demand in bottles rather than cases. Otherwise, it's the same as Problem The MRP records for Compound W and Chemicals X & Y are in ounces. To complete this problem correctly, you must understand how much Chemical X and Y is in each ounce of Co

Full bottles Master Schedule Start Assembly

Bottles Gross Requirements Scheduled Receipts Projected ending inv. Net Requirements Planned receipts Planned orders Caps Gross Requirements Scheduled Receipts Projected ending inv. Net Requirements Planned receipts Planned orders Compound W (ounces) Gross Requirements Scheduled Receipts Projected ending inv. Net Requirements Planned receipts Planned orders Chemical X Gross Requirements Scheduled Receipts Projected ending inv. Net Requirements Planned receipts Planned orders Chemical Y Gross Requirements Scheduled Receipts Projected ending inv. Net Requirements Planned receipts

1 25,800 0

5,000

2,000

0 0

0 14,400

5 14,400 0

6 0 15,600

4 14,400

0 0 0 9,000

9,000 0 0 12,000

3,600 5,400 9,000 0

3,600 0 0 0

0 12,000 12,000

5 0

6 15,600

4 14,400

5,000 0 0 0

5,000 0 0 50,000

40,600 9,400 50,000 0

40,600 0 0 0

25,000 0 0 0

3 0

4 86,400

6 93,600

2,000 0 0 0

2,000 0 0 84,400

0 84,400 84,400 0

0 0 0 93,600

0 93,600 93,600 0

3 56,267

5 62,400

0 0 0 0

0 0 0 56,267

0 56,267 56,267 0

0 0 0 62,400

0 62,400 62,400 0

15,000

0 0

0 9,000 9,000 0 0 0

0 0

WEEK 4

0 0 0 0 0

5 31,200

3 28,133

0 15,000 0 0

15,000 0 0

66,867 13,133 80,000

66,867 0 0

35,667 0 0

Planned orders

80,000

*** KEY ***

and scheduled receipts

rwise, it's the same as Problem 1.

X and Y is in each ounce of Compound W.

7 15,600 0

0 0

0 0 0

8 0

25,000 0 0 0

25,000 0 0

8 0

0 0 0 0

0 0 0

8 0

0 0 0 0

0 0 0

8 0

35,667 0 0

*** Problem Set Key -- Do Not Post or Distribute *** Chapter 12: Managing Production Across the Supply Chain Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd DIRECTIONS

To generate the key, input the same four-digit number used to generate the original homework set. The correct answers will be calculated automatically. Name: *** Key *** 4-digit number: 7654 Northcutt puts together foot pedal assemblies using components they buy from outside suppliers. Below is the bill of material (BOM) for the foot pedal assembly. Some foot pedal assemblies are used in production, many are sold to other manufacturers, and the rest are sold as replacements. Foot pedal assembly

Pedal Body Pedal Top

Problem 1

Acorn Nut

Spindle

Pedal Bottom

Complete the master production schedule for foot pedal assemblies, shown below.

346 Foot pedal assemblies

On-hand inventory at end of December = Month / Week Forecast Demand Orders Booked Projected on-hand inventy Master schedule Available-to-promise

Problem 2

Acorn Nut* * 2 needed here

******** January **********

******** February **********

1 3,460 3,010

2 3,460 2,387

3 3,460 1,903

4 3,460 3,806

5 3,806 1,446

6 3,806 837

7 4,152 1,038

3,806 6,920 1,869

346 0

346 3,460 1,557

7,610 11,070 4,981

3,804 0

-2 0

4,146 8,300 6,640

Look at your answer to Problem 1. Suppose a customer calls up & asks to place a new order for 2,700 assemblies in Week 1. How many of these foot pedal assemblies can Northcutt promise? Justify your answer below.

Available to promise for Weeks 1 through 2 =

1,869

Therefore, Northcutt Bikes can send them 1,869 now. Any additional units would have to wait until Week 3.

& Handfield, 3rd Ed.)

from outside

manufacturers,

assemblies

8 4,152 622 -6 0

assemblies

*** Key ***

Problem 3

Complete the MRP for foot pedal assemblies, based on the above MPS quantities. (I have already filled in the MPS due date information for Week 1; you can assume that all the manufacturing steps have been completed for these 6920 pedals.

*** Pedal Assemblies *** LT (weeks) = 1 MPS Due Date Start Assembly Pedal Body LT (weeks ) = 1

Min. Order = 1 (lot-for-lot) Spindle LT (weeks ) = 5

Min. Order = 2000

Acorn Nut LT (weeks ) = 1

Min. Order = 30,000

Pedal Top LT (weeks ) = 2

Min. Order = 5000

Pedal Bottom LT (weeks ) = 2

Min. Order = 1000

Gross Reqmts. Sched. Receipts Proj. On Hand Net Reqmts. Planned Receipts Planned Order Gross Reqmts. Sched. Receipts Proj. On Hand Net Reqmts. Planned Receipts Planned Order Gross Reqmts. Sched. Receipts Proj. On Hand Net Reqmts. Planned Receipts Planned Order Gross Reqmts. Sched. Receipts Proj. On Hand Net Reqmts. Planned Receipts Planned Order Gross Reqmts. Sched. Receipts Proj. On Hand Net Reqmts. Planned Receipts Planned Order

6920

3460

17436

WEEK 4

6920 0

0 3460

3460 11070

11070 0

0 0

3460

11070

0 0 0 3460

0 3460 3460 11070

0 11070 11070 0

0 0 0 0

0 0 0 8300

11070

0 0 0 6847

3460 15983 12523 0 0 0

1453 0 0

3460

17990

22140

8300

0 0 0 30000

12010 17990 30000 30000

19870 10130 30000 0

19870 0 0 0

11570 0 0 30000

3460 14530 11070 0 0 0

11070

8300

0 0 0 0

0 0 0 8300

0 0 0 0

0 8300 8300 0

3460

11070

8300

13976 0 0 0

2906 0 0 0

2906 0 0 5394

2906 0 0 0

0 5394 5394 0

assume that all the

0 8300

8300

0 8300 8300 0

0 0 0

8300

0 6847 6847

0 0 0

16600

24970 5030 30000 0

24970 0 0

0 0 0

*** Problem Set Key -- Do Not Post or Distribute *** Chapter 13: JIT / Lean Production Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd Ed.) DIRECTIONS To generate the key, put the same 4-digit number used when printing off the original assignment. Name: *** KEY *** 4-digit number: 5000 50

The Oxford Company wants to set up a kanban system linking it with one of its key local suppliers. The part that Oxford sources from the supplier costs $11.50 per unit, and Oxford uses about of the parts per hour. The supplier lead time is about 6.5 hours, & each container holds parts. Problem 1

How many kanban cards does the Oxford Company need to link itself with the supplier, assuming no safety factor? How many hours worth of inventory does this translate into? Show your work in the space below.

kanban cards = D*T (1 + safety factor) / Container Size = which rounds up to This number of cards translates into

14.50 cards, 15 cards

7500 units, or 6.73 hours of inventory

"Rounding up" the no. of kanban cards often creates some safety stock.

Problem 2

Now suppose the Oxford Company decides that it wants to incorporate a safety factor of 20% into the calculation. What is the new number of kanban cards? Show your work in the space below.

kanban cards = D*T (1 + safety factor) / Container Size = which rounds up to This number of cards translates into

17.39 cards, 18 cards

9000 units, or 8.07 hours of inventory

andfield, 3rd Ed.)

al suppliers. 1115 500

ventory does

e a safety factor of Show your work in

*** Problem Set Key -- Do Not Post or Distribute *** Chapter 14: Managing Projects Introduction to Operations & Supply Chain Management (Bozarth & Handfield, 3rd Edition) DIRECTIONS To generatethe key, put in the same 4-digit number used in printing out the original assignment. Name: *** KEY *** 4-digit number: 8000 80 Problem 1

Consider the project network diagram shown below. Using this diagram and the activity duration times listed below, calculate the ES, EF, LS, and LF times for all activities. In addition, identify all critical activities. How long will the project take? H B G C A

K I

M L

J F

Activity A B C D E F G H I J K L M

Duration Earliest (days) Start (ES) 4 0 11 4 6 4 7 4 4 10 5 11 6 15 7 21 4 21 5 16 6 28 7 21 4 34

The project will take

Earliest Finish Latest (EF) Start (LS) 4 0 15 4 10 5 11 10 14 11 16 17 21 15 28 21 25 30 21 22 34 28 28 27 38 34 days

Latest Finish (LF) 4 15 11 17 15 22 21 28 34 27 34 34 38

Critical Activity? Yes Yes

Yes Yes