One-Piece Flow Doesn’t Fit All (or Even Most)

July 11, 2023
Exceptions are actually the rule for this widely accepted process improvement strategy.

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One-piece flow (OPF) is axiomatic among lean practitioners. We’ve all seen the illustrations (like this one) that show the advantage of one-piece flow. There are several of this sort of animated illustrations around (here’s another). They all make the same comparison: Moving a batch of pieces through several process steps is contrasted with moving one piece at a time through several process steps. The “one-piece flow” version always wins.

Given that the concept of “one-piece flow” has been around for a long time and that there are so many illustrations of its efficacy, why don’t more manufacturers employ it? The quick answer is: There aren’t many manufacturing operations that look like the illustrations.

Take a look at either of the animations of one-piece flow linked to above. Rick has had only one client whose operations remotely resemble that particular flow. That client assembled a popular kitchen appliance using a long line of assemblers, each of whom completed a well-defined task, then passed the work to the next assembler.  

On the other hand, another client made a variety of craft beers. One-piece flow wasn’t relevant.  Craft-beer batches can be as small as a plastic five-gallon bucket or as large as a three-story-high stainless steel tank. In either case, the beer has to stay in that bucket or tank somewhere between three days to three weeks, depending on the style of the beer. It’s no faster to move five pints of beer through the fermentation process than it is to move 5,000 gallons.  It makes sense to increase the batch size in this case.

Even Rick’s client who made and marketed artisanal women’s clothing of unique designs wasn’t able to use one-piece flow. It doesn’t make sense to color and dye cloth for one dress at a time.  The amount of time needed to dye the material for 100 dresses isn’t appreciably longer than the time it takes to dye the material for one dress. It makes sense to dye the material for all 100 dresses in as few batches as possible.

Other Exceptions

One-piece flow isn’t relevant at all to process manufacturing. It’s not useful for processes that include heat treating. Even in those cases where OPF is relevant, movement and transportation of one piece at a time is problematic unless the process steps are immediately adjacent, as the assemblers of the appliance were.   

Managers can be excused, then, if they look at the “one-piece flow” illustration and rationally decide that it doesn’t fit their circumstances.

“One-piece flow” acolytes are right about one thing; smooth, consistent flow of material and product is the ideal to be achieved in any process. But batch production, in and of itself, doesn’t impede flow. In nearly all the illustrations I’ve seen, even though larger batches are completed in less time, the flow is smooth and consistent. That means they can be scheduled with confidence that they’ll be started and finished on time. That, in turn, means that the manufacturer can provide the customer with a shipping date that they can be sure they can stick to. And that’s what the customer is paying for. Fast flow is great, but smooth, consistent flow is more important. So, rather than “one-piece flow,” lean practitioners should simply advocate for “smooth, consistent flow.”  

Inconsistent, variable flow isn’t generally the result of “not one-piece flow.” Rather, it’s the result of variance in the process. Delays, scrap, rework, unavailable materials, tooling, equipment and information are examples of process variance that disrupt smooth flow. They will disrupt smooth flow whether the batch size is one or one million.  

The key, then, isn’t so much to reduce batch size as it is to reduce (or eliminate, where possible) process variation. 

Shorter Can Be Better

Ron once led a plant that molded polycarbonate ophthalmic lenses. He and his colleagues embarked on an initiative using six sigma tools and methods to reduce process variation. That initiative resulted in improved first-pass yields, which enabled shorter runs to produce the needed inventory. Shorter runs (smaller batches) facilitated better product mix and inventory that was better matched to customer demand. The improved inventory management and control allowed higher fulfillment rates and lower shipping costs.

But, you might reasonably ask, can’t a desire to reduce batch sizes motivate the reduction of variation? Yes, it can. In fact, that’s a good reason to set a goal to reduce batch sizes. Too often, managers use long runs to build inventory as buffers to the variation that they know is embedded in their processes. If reducing batch sizes gets rid of those buffers such that managers are forced to address the process problems, so much the better.  

Our point, then, isn’t that manufacturers don’t need to pay attention to batch sizes. Large batch sizes can be a symptom of too much variance within manufacturing processes. Rather, our point is to encourage manufacturers to analyze their production processes so as to identify variances, then determine their sources. As manufacturers carry that project out, they’ll find that they can reduce batch sizes.  

 Ron Jacques is a 35-year veteran within the lean, manufacturing and consulting arenas. He is a certified lean practitioner who has delivered hundreds of kaizen and transformational solutions to clients and companies within the Pharma, Medical Device, Automotive, Food/Beverage, Electronics, Military Defense, Personal Care, Consumer Durables and Capital Equipment industries.

 Rick Bohan, principal, Chagrin River Consulting LLC, has more than 25 years of experience in designing and implementing performance improvement initiatives in a variety of industrial and service sectors. He is also co-author of  People Make the Difference: Prescriptions and Profiles for High Performance.

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About the Author

Rick Bohan | Principal

Rick Bohan, principal, Chagrin River Consulting LLC, has more than 25 years of experience in designing and implementing performance improvement initiatives in a variety of industrial and service sectors.

Bohan has a bachelor of arts in psychology from the University of North Carolina at Chapel Hill and a master of science in organizational development from Case Western Reserve University in Cleveland. He has published articles in National Productivity Review, Quality Progress and ASTD's Training and Development Journal. He is also co-author of People Make the Difference, Prescriptions and Profiles for High Performance. Bohan can be reached at [email protected].

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