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Lean Production Control: Pull SystemsOctober 1, 2005 Two months ago, I wrote an article about one-piece flow, which is one of the most important principles of lean manufacturing. This month's article deals with controlling production in areas where one-piece flow is impossible. Recall that, in order for one-piece flow to work, the processes must be highly capable, highly repeatable, and almost always available (high uptime). Additionally, processes must have very low changeover times and must be able to run to takt time. There are many processes that do not meet these criteria. For example, processes such as injection molding, metal stamping, and heat treating often cannot be scaled to run at takt time. Metal stamping and injection molding processes often run faster than takt time, and heat treating often runs much more slowly than takt time. These processes usually have long changeover times. Thus, they are batch-and-queue processes by design. How does the lean manufacturer control production for such processes? While the mass producer controls production using a traditional push system in which each manufacturing area is scheduled independently based on an MRP forecast, the lean producer uses a pull system. That is, the batch and queue processes will replenish a supermarket of parts that would be consumed by a downstream one-piece flow process (such as final assembly). The downstream process withdraws parts from the supermarket. As parts are consumed and a trigger point for replenishment is reached, an order is then sent to the upstream batch process, which runs a batch of product to replenish the supermarket. Below is an illustration of a plastic injection molding process replenishing a supermarket of plastic parts from which two one-piece flow cells withdraw parts.
A replenishment pull system is not always the solution for production control within a lean producer's value stream. While replenishment pull systems work well in many cases, for highly customized products or job shop environments, such pull systems are rarely the right solution. Consider a job shop whose customers are ordering one-of-a-kind products in low volumes. Customization would make supermarkets impractical for controlling inventory between processes. Instead, an alternative such as a FIFO lane (sequential pull) might be implemented. A FIFO lane is a buffer that can be used to hold a certain amount of inventory between an upstream (supplying) and downstream (consuming) process. Unlike a supermarket, it does not hold a certain quantity of particular inventory; it holds a certain quantity of total inventory. Items are pulled in sequence from the FIFO lane. When the lane is full, the supplying process stops producing parts. A FIFO lane is sometimes an actual lane on a factory floor in which parts can accumulate. There are other alternatives to and variations of pull systems as well. For example, a pseudo-lean manufacturing methodology developed at the University of Wisconsin, called QRM (Quick Response Manufacturing), uses POLCA. It combines elements of FIFO lanes (limiting the amount of production) with replenishment pull systems (using kanban/cards). It is important to customize any approach to controlling production to suit the needs of your organization. A traditional pull system is not a recipe for success but rather a principle to be followed in controlling production. Click here to subscribe to our free e-newsletter Learning to Lean and receive three articles like this one each month. About the Author Darren Dolcemascolo is an internationally recognized lecturer, author, and consultant. As Sr. Partner and co-founder of EMS Consulting Group, he specializes in productivity and quality improvement through lean manufacturing. Mr. Dolcemascolo has written the book Improving the Extended Value Stream: Lean for the Entire Supply Chain, published by Productivity Press in 2006. He has also been published in several manufacturing publications and has spoken at such venues as the Lean Management Solutions Conference, Outsourcing World Summit, Biophex, APICS, and ASQ. He has a BS in Industrial Engineering from Columbia University and an MBA with Graduate Honors from San Diego State University. | |||||||||||||||||
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