IT VIEW

Demand-Driven Smart Manufacturing

By John Clemons

Director of Manufacturing IT, Maverick Technologies

The new MESA International Smart Manufacturing Model is under development and will be released very soon. It’s different from other smart manufacturing models out there in that it’s not academic, it’s not descriptive, and it’s not meant as a reference to sit on the shelf.

It’s prescriptive, providing very specific recommendations on how we can be smarter in managing the lifecycles of manufacturing operations. It provides recommendations on the lifecycles that impact manufacturing operations including supply chain, personnel, order to cash, product, production, and production assets.

One question that’s addressed by the new model is “how can production be agile enough to respond to variability in demand from the enterprise without maintaining costly and risky finished goods inventory?”

The four key approaches to manufacturing are: Produce on demand, make to order, engineer to order, and make to stock. However, almost by definition, make to stock is not agile and it never will be. Even make to order and engineer to order, depending on how, when, and why the orders are created may not be as agile as claimed. The smart move is produce on demand, but that’s a lot easier said than done.

It means you must really know what the demand is, and you must modify your production processes to meet that demand. It means you produce what’s needed when it’s needed. You produce the right quantity at the right time. It’s not capacity driven in the least—it’s totally demand driven. That’s what makes it agile. It’s easier said than done, but well worth it in the long run.

Another questions that’s addressed by the new model is “what’s the best way to ensure that the production resources are used most effectively to meet the demand from customers?”

There are several aspects to this question. One is how forecasting, planning, and scheduling are done. Many good technologies exist in the smart manufacturing toolkit that can help in this regard, but you have to use them, and you have to use them well. That means looking at the resource allocations and the resource assignments. This includes all the resources: personnel, assets, materials, consumables, logistics, etc., and then assigning and allocating those resources in a smart fashion.

It also means looking at the suitability of the resources, the capability of the resources, the availability of the resources, the capacity of the resources, and so on. It means you have to know your resources—all of them—know what they can do, and what they can’t do, and allocate them effectively and efficiently.

Other questions addressed by the new model are “how can we make sure that finished goods and product coming out of production are consistently high quality?” It also addresses how to deal with a regulatory agency (e.g., the FDA) requiring detailed documentation of every step taken in the production processes,

When it comes to production quality, its important to recognize that testing has its place. But quality has to be built in, not tested in. The production process must be built to be error proof and self-correcting to ensure that quality is built in at every step. That means operators must know exactly what quality means and what it takes to produce a quality product. When this occurs, testing is simply done to verify that the product meets the quality requirements.

Of course, it’s necessary to capture test results and identify exceptions when they occur. It’s also necessary to track incidents and deviations and have a continuous improvement process in place to take the information from the exceptions and deviations and work to eliminate the possibility of them ever occurring in the first place. Here, too, the reasoning is that your processes should be all about building in quality, not simply testing for it after the fact.

Another question that’s addressed by the new model is “how does smart manufacturing make it easier to deal with new product introductions and high product mix situations?”

The answer is to be smarter when it comes to product design, management and transformation of recipes, creation and dissemination of product specifications and work instructions, management of the bills of materials, and management of the linkages of all these items to each other and to the other elements of the production lifecycle.

One final question I’d like to mention that’s addressed by the new model is “can smart production techniques ease the burden of workforce and skills shortages?”

The key here is having highly skilled, highly trained, high-performing resources, who have the right skillsets, and the right resources and tools at their fingertips. Then, it’s making sure those resources are in the right place at the right time.

So, if you’re intrigued by these questions, and are looking for more answers than I’ve had space to mention, then the new MESA International Smart Manufacturing Model is for you.

Quality has to be built in, not tested in. T�e production process must be built to be error proof and selfcorrecting to ensure that quality is built in at every step. T�at means operators must know exactly what quality means and what it takes to produce a quality product. W�en this occurs, testing is simply done to verify that the product meets the quality requirements.