SIX SIGMA APPLICATION IN KETCHUP INDUSTRY FOR DAMAGED GLASS BOTTLES: A CASE STUDY

International Journal of Mechanical and Production Engineering Research and Development (IJMPERD) ISSN (P): 2249–6890; ISSN (E): 2249–8001 Vol. 10, Issue 3, Jun 2020, 3397-3406 © TJPR Pvt. Ltd.

SIX SIGMA APPLICATION IN KETCHUP INDUSTRY FOR DAMAGED GLASS BOTTLES: A CASE STUDY YATHARTH SHARMA, SARMAD HASSAN & RAJAT KUMAR Delhi Technological University, New Delhi, India ABSTRACT The aim of this paper is to examine the problem of loss incurred due to damage of glass bottles in the tomato sauce/ketchup industry which not only results in depreciating economy to the manufacturer but also degrades the reputation of a company and degrades its image. This paper uses the DMAIC methodology which is a part of Six Sigma for evaluating the problem. The identification of the root causes was done using Kaoru Ishikawa Diagram (Fish Bone Diagram). The weight of individual root cause was calculated using Analytical Hierarchy Process (AHP). Pareto Chart was established to figure out the root causes of the greatest consequence, which were having a very significant impact on the deliverables. Subsequently, brainstorming was done with the experts of this field including the department of Quality Control and logistics was organized which facilitated in figuring out the solutions by reviewing the process map. This paper has been the first attempt to find and review the root causes of the problem of Glass Bottles damage in this given under Six Sigma methodology.

KEYWORDS: AHP, DMAIC, Industrial Management, Lean Management, Quality Control & Six Sigma

Received: Jun 20, 2020; Accepted: Jul 01, 2020; Published: Jun 14, 2020; Paper Id.: IJMPERDJUN2020323

Original Article

particular industry and suggest solutions so that there is a decline in the quantity of damages using DMAIC approach

1. INTRODUCTION Six Sigma is a useful methodology for problem-solving. It gives a valuable measurement approach. Six Sigma has a mathematical base, which, with proper utilization of methodologies, can help in refining the quality of both the process and the product. The basic goal of this methodology is the application of a strategy based on measurement focused on improving the process and reducing variation by applying specific projects. Managers in the food industry have to thus focus on maintaining profitability in a reducing market, along with providing efficient service and good quality products to increasingly sophisticated buyers. In order to accomplish this apparently unattainable goal, companies can choose two strategies. First, they can improve their system's operational efficiency. Second, they can take proper steps to improve its operational quality.

2. CASE STUDY This case study is performed at Company XYZ which is a leading ketchup bottle manufacturer in India. The DMAIC methodology is applied below. To the best of our knowledge, no research work is done till date to resolve the problem of damage of Glass Bottles in Ketchup industry.

2.1 Define Phase 2.1.1 Problem Statement To reduce the quantity of damaged glass bottles from 9,830 in the preceding year to 4,200 in the next year.

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2.1.2 Business Case Company XYZ has experienced 9,830 damaged glass bottle units in the preceding year worth of INR 1,100,000/-. This has resulted in the followingdirect cash losses to the company. These losses are mentioned in table 1.

Table 1 Particular Loss of Glass bottle cost Loss of cost of extra engagement of labor Loss in revenue due to devaluation of the product Total Loss

Loss Amount (INR) 70337 /44322 /126632 /241,291 /-

Therefore, loss from each bag damaged= INR 241,291 / 9830 =INR 24.54/2.1.3 Process Map The sequence in which the movement of bag takes place and its sub process map is shown in figure. 1 2.2 Measure Phase After this tool of data analysis, we use AHP to find the weightage of each root cause followed by use of Pareto Chart to prioritize our resources and direct attention to vital root causes.

The cause & effect relationship shown in figure 2 below can occur at the vendors point, in transit between vendors point and main store, at the main store, in transit between main store and filling station and at the filling station. Whereas the causes & effects relationship shown in figure. 3 can occur at the filling station, in transit between filling station and warehouse, in transit between various warehouse positions, in transit between warehouse and platform, at platform, in transit between platform and truck, at truck during transit between plant and point of unloading and at the point of unloading.

Figure 1: Process Map and Sub-Process Map (Glass Bottle).

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Figure 2: Fish Bone Diagram (Unfilled Bottles).

Figure 3: Fish Bone Diagram (Filled Bottle).

2.3 Analysis Phase Due to similarity between the root causes, they are combined together under six main heads, which from here onwards will be identified as the root causes. First root cause is Storage defects (ST) which includes improper management of space which may cause defects during movement of forklifts. Second root cause is Transportation (T) which is very important to consider since the products are fragile and can break if not taken care properly. It includes improper loading/unloading practice, poor maintenance of trucks, too much jerk and vibration during transit, etc. Third root cause is Production (P) where defects can arrive due to unskilled labor, improper production techniques, etc. Fourth root cause is Packaging (PG).

Fifth root cause is lack of Attention and Supervision (S) at multiple stages like filling station, loading/unloading. Sixth root cause is issues during Inspection (IN), this may be due to non-maintenance of Inspecting machines, false positive inspection, etc.

2.3.1 Weight Age Calculation using ahp Weightage of every individual root cause is calculated using AHP (Analytic Hierarchy Process). AHP is designed tosolve www.tjprc.org

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complex multi criteria problems. Many quantitative approaches have been taken into observation to evaluate new technology implementation. Table 2 depicts the pairwise combination of each of the root cause. The fraction obtained in table 2 is converted into decimals as presented in table 3. On the basis of these pairwise combinations, iterations are performed till we obtain consistency ratio of less than 0.1 (If the consistency ratio is more than 0.1, then the data provided is not reliable). These iterations is shown in table 4.

Table 2: Pairwise Combinations of Each Root Cause ST T PR PG S IN ST 1 1/4 1/3 1/2 1/3 1/5 T 4 1 2 5 3 4 PR 3 1/2 1 2 1 1/3 PG 2 1/5 1/2 1 1/5 1/2 S 3 1/3 1 5 1 3 IN 5 1/4 3 2 1/4 1 SUM 18 2.533 7.833 15.500 5.783 9.033 Table 3: Pairwise Combination of Root Cause In Decimals ST T PR PG S IN ST 0.055 0.098 0.042 0.032 0.057 0.022 T 0.222 0.394 0.255 0.322 0.518 0.442 PR 0.166 0.197 0.127 0.129 0.172 0.036 PG 0.111 0.078 0.063 0.064 0.034 0.055 S 0.166 0.131 0.127 0.322 0.172 0.332 IN 0.277 0.098 0.382 0.129 0.043 0.110

ST T PR PG S IN

ST 0.051 0.206 0.154 0.103 0.154 0.257

T 0.090 0.359 0.180 0.072 0.120 0.090

PR 0.046 0.277 0.138 0.069 0.138 0.415

Table 4: Checking For Consistency Weighted PG S IN Sum Average 0.034 0.070 0.035 0.326 0.340 0.627 0.695 2.504 0.136 0.209 0.058 0.875 0.068 0.042 0.087 0.441 0.340 0.209 0.521 1.483 0.136 0.052 0.174 1.125

Criteria Weight 0.051 0.359 0.138 0.068 0.209 0.174

λ 6.331 6.967 6.325 6.476 7.099 6.473

After taking the average value of𝜆, we get 𝜆(𝑎𝑣𝑔)=6.611 𝐶𝑜𝑛𝑠𝑖𝑠𝑡𝑒𝑛𝑐𝑦 𝐼𝑛𝑑𝑒𝑥 (𝐶𝐼) =

𝜆(avg)−𝑛 𝑛−1

= 0.122366

𝐶𝐼

𝐶𝑜𝑛𝑠𝑖𝑠𝑡𝑒𝑛𝑐𝑦 𝑅𝑎𝑡𝑖𝑜 = 𝑅𝐼 = 0.098682 Where RI is Random Index and is fixed as 1.24 for matrix size (Factors) of 6. Since the consistency ratio is less than 0.10, we can say that our matrix is reasonably consistent.

ST T PR PG S IN

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0.05 0.36 0.14 0.07 0.21 0.17

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Table 5: Values of Pareto Chart Figure 4: Pareto Chart (Weightage of Each Root Cause).

2.3.2 Analysis of Weight Age of each Root Cause Figure 4 shows analysis of root causes through their weightage obtained from AHP, as shown in table 5 It can be understood from the pare to chart that Transportation (T) and Storage (S) combined accounts for more than half of the loss due to damaged bottles. Other major root cause being Inventory (IN). Remaining root causes (PG & ST) account for just 20% of the loss. Giving due priority to T, S, IN can cover upto 3/4th of the total loss due to damaged bottles. CE being the only factor on which the company will have least control because the product is FMCG and it spent less time in company warehouse.

2.3.3 Analysis of Loss that is Associated with each Root Cause Through the weightage calculated from AHP, we now deduce the loss related with each root cause by multiplying their weightage with the total no. of bags damaged bottles. This gives us the no. of bottles damaged due to each root cause or the loss related with each root cause in INR, since, we know the cost of each bottle damaged (As calculated in the business case).Table 8 shows this analysis. Furthermore, table 8 is represented in the form of a Pareto chart shown in figure. 6 which high lights the importance of each root cause in monetary terms. From figure 6 it is clearly visible that our target of reducing loss due to bottle damage by 43% is easily achievable by primarily focusing on 3 main root causes, namely, T, S and IN.

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Figure 5: Pareto Chart (Losses Linked With Each Root Cause).

Table 6: Values of Pareto Chart Root Cause Weight Age No. of Bottles Damaged Loss Amount (INR) ST 0.05 492 12064.55 T 0.36 3539 86864.76 PR 0.14 1376 33780.74 PG 0.07 688 16890.37 S 0.21 2064 50671.11 IN 0.17 1671 41019.47 Since cost of each glass bottle damaged = INR 24.54 /- (Illustrated in the Business Case) 2.3.4 Date wise Analysis of 12-Months Data It is important to analyze the point of time during the month at which glass bottle damage takes place. This helps us in verifying the practicality of our interpretations of figure 4 and figure 5. Table 8 gives a 12 months data of summation of glass bottle damage on each of the date. Table 8 is represented in the form of a paretochart in Figure. 6 which is not following the decreasing trend since we need to analyze the trend across the month. It is clearly visible that in the second half of the month, due to excess movement of the glass bottles and lower rate of attention by staff on each bottle, more bottles get damaged. This verifies our claim that over majority of the losses due to bag damage can be prevented if three root causes T, S and IN are properly focused on, along with brief attention to the issue of maintenance.

2.4 Improve Phase In order to reduce loss due to bags getting damaged, following solutions are suggested in table 7.

Table 7: Suggestions from the Improve Phase S. No.` 1 2 3 4 4 5 6 7 8 9 10 11

Solutions Proper loading &unloading procedures must be followed Training to the workforce and regularly briefing by supervisor in order for cheering up morale.

Trucks must be serviced properly so that its suspension system does not becomes stiff More number of testing must be done, Proper training must be provided to the driver Solving the points of bottlenecks in order to become more efficient, automated monitoring of the production processes reducing false positive reports of the empty bottles Gentle handling of the bottles, prevention of collision of bottles from each other Warehouse and production plant must be organized properly so that space management can be done Prevent overloading of the trucks and forklift Give proper guidelines for proper handling of the bottles Give workforce adequate breaks and manage proper work-life balance

Target Cause T S T IN T PR IN PG ST T/ST/S S S

2.5 Control Phase The aim of this project was to bring back the focus of the management to surge in losses due to surge in the amount of glass bottles getting damaged. Thus, this project has identified not only the root causes but also direct financial loss due to each of the root cause of this problem. Solutions based on interpretations of the pareto chart have been accepted and implemented. For sustenance of results, the new process was standardized, documented, and distributed at every department to execute on a daily basis. Additionally, the ongoing performance was reviewed till it became part of an everyday daily process.

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Date 1 2 3 4 5 6 7 8

Table 8: Pareto Chart (Date wise Analysis of 12-Months Data Damaged Bottles Date Damaged Bottles Date Damaged Bottles Date 146 9 235 17 378 25 204 10 137 18 598 26 116 11 278 19 478 27 118 12 248 20 446 28 198 13 221 21 364 29 273 14 464 22 398 30 489 15 443 23 287 31 263 16 489 24 345

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Damaged Bottles 376 312 289 256 221 309 451

Figure 6: Pareto Chart (Date wise Analysis of 12 Month Data).

3. CONCLUSIONS This study is performed to classify and examine the main causes of the problem of Glass Bottle damage in Ketchup/Tomato Sauce industry and suggest solutions to reduce damages.

In order to recognize opportunities for improvement, a process map was documented. Root causes were recognized with the support of fish-bone diagram. Weightage of each root cause was calculated using analytical hierarchy process and a pare to chart aided to focus attention on the most pressing root causes.

Accordingly, brainstorming was performed with the production, warehouse, logistics and quality control section was done which helped in framing the solutions by examining the process map.

Although this is one of the first attempts to focus on the problem of Glass Bottle damage, academics and practitioner could use this study for future study in other industries where Glass Bottle are used. Future research can be conducted by calculating the weightage of each root cause using paired comparison method or balanced score card method.

A follow up on the level of lean implementation and cultural change in the companies addressed in this study is advised.

Also, specifically concerning other causes, future work may focus on more accurately quantifying the impact of machine design changes and the impact in inventory reduction. Finally, another interesting research avenue may be comparing Lean Management implementation results among companies of different sectors. This would allow further understanding the

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potential and importance of process innovation in different industrial contexts.

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AUTHOR’S PROFILE

Yatharth Sharma received the B.Tech Degree in Mechanical Engineering from Delhi Technological University, in 2019.

He was a former member of the team DTU AUV, SAE and ISHRAE. His interests include playing badminton, counselling on career paths and Industrial Engineering applications. He worked with Hilti India as GET and in Mercedes-Benz, EIL, Air India and Pawan Hans as intern and developed skills related to the defence industry equipment manufacturing.

Rajat Kumar received the B.Tech Degree in Mechanical Engineering from Delhi Technological University, in 2019. He was a former BAJA member of the team DelTech BAJA. His interests include designing the transmission system in BAJA vehicles, application of Input-Output Model for End-of-Life-Vehicles in India, thermodynamics and Industrial Engineering applications. He worked with Bharat Electronics Limited as intern and developed skills related to the defence industry equipment manufacturing.

Sarmad Hassan received the B.Tech Degree in Mechanical Engineering from Delhi Technological University, in 2019.

He was a former member of ISHRAE. His interests include designing UAV and Robotic systems and Industrial www.tjprc.org

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Engineering applications. He worked with Omnipresent Robot Tech as intern and now as a design engineer and developed skills related to the defence industry equipment manufacturing.

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