My last two posts in this three-post series on leveling talked about fluctuations and leveling in general, and the challenges and costs associated with leveling. In this last post I will go into greater detail on how Toyota does its leveling. Because Toyota does this actually quite well.
In my last post I gave you a brief introduction to fluctuations and leveling. And, I already hinted that there are two downsides to leveling: properly set up it handles only fluctuations coming from upstream, and—what is rarely talked about—there is an increase in inventory and/or waiting time to decouple the fluctuations in leveling. The second one especially is widely ignored or even vehemently denied in industry, but it is definitely there. Let me show you!
Leveling (or Japanese heijunka) is a common topic in lean manufacturing. Leveling combats one of the three evils in manufacturing: unevenness or fluctuations (in Japanese mura). While reducing fluctuations is an excellent goal, it is unfortunately not free, and there is significant effort not only for implementing and maintaining the leveling system, but also on the way the fluctuations are reduced. While everybody talks a lot about the benefits of leveling, very few talk about the cost. This may be one reason why so many leveling systems fail. Let me show you the hidden not-so-nice side of leveling.
In my last post, I started to look at factors that affect the efficiency of your line, in particular the percentage of value-added time by the operators. For this I have a good data set with fifty-three different observations. One major factor was the speed of the line. Faster lines are not only easier to optimize, but they also yield more benefit for the optimization. In this post I will look at group size, as well as comparing Japan and Germany, final assemblies with subassemblies, and passenger cars with commercial vehicles.
Whenever I visit a factory where manual work is done, I try to estimate the percentage of value-adding time. This brings up an interesting question: What factors do affect the percentage of value-adding time? Let’s dig through my data to see what matters.
In my last post I described a quick-and-dirty approach to estimate the percentage of value add (i.e., the efficiency) of manual work. While the value is only an estimate, it is a measurement that you can take quickly and easily even in passing for a manual workplace. You simply count when a person is adding value and when not (i.e., waste). This post will look into more detail on what numbers to expect, and what to do next if you want to increase this percentage of value adding time. Let’s have a look:
One of the necessary tasks in becoming leaner and improving your industry is to eliminate waste. I like to use a simple approach for measuring waste in manual work to know how good (or bad) the current situation is. To explain my approach I commissioned a few animations. Let me proudly present my approach and my animations, so you can also estimate the efficiency of manual lines when you are on the shop floor.
After an introduction and description of the fundamentals of karakuri kaizen, here are some different karakuri kaizen examples for a wide variety of uses. Most of them are from the 480 exhibits at the the Karakuri Kaizen Exhibition 2017 in Nagoya, Japan; others are from the 2017 OPEXCON in Stuttgart, Germany. Here is my attempt of a structured overview, even though some of the points below may be overlapping.