A Simple Kaizen Event Yields Productivity Increase of Almost 100%

A Simple Kaizen Event Yields Productivity Increase of Almost 100%

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  • On January 30, 2015
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A Simple Kaizen Event Yields Productivity Increase of Almost 100%

In any business, it is important to constantly keep on top of things that could improve the company’s output. Kaizen events, or changes made for the greater good, are constantly occurring in any established factory or business. However, you can’t just make random changes. In fact, there is a set formula used for such events. For example, it’s important to first examine the problem and identify areas where production may be backed up or slowed down.


One of the surest ways to identify a bottleneck is to look for excess inventory. While walking the plant one day, I noticed more trays in one area than I thought should be there. I walked to another area of the plant where the upstream process was performed. There I saw even more inventory.


The next step in the process is to clearly document the problem. After finding all of that excess inventory, it was clear that I needed to dig into the issue further.


After completing my research, I had the following data:

  • Daily production: 300-400 units per shift
  • Operators in the cell: 3 per shift
  • Production goal: 700/shift
  • Total inventory to-be-processed: more than 10,000 units, 25-33 shifts worth of production


Clearly, something needed to be done. However, the operators had to be consulted, since any changes made would directly impact their daily work routines. Their input was absolutely vital. In fact, they had numerous ideas on how to improve the cell. For example, the operators commented about how hard they had to work. That sounds like they were complaining but they were not. Instead, they exposed a symptom of the problem. They were required to walk too far each day because of how far apart the machines were spaced. That was an easy problem to fix.


Though the preference is to implement only the suggestions the operators agree with, sometimes other actions are required. In this case, we had to address one piece flow. In this process, there were three machines and five total processes. The operators were batching parts after most of the processes. Now that the machines were closer together, we thought one piece flow would drastically improve output.


In order to persuade the operators, we asked them to use one piece flow for one shift. After that shift, there were numerous suggestions. But those suggestions were expected. That’s exactly why we made that change. Producing one piece at a time made the inefficiencies more visible and easy to attack. We proceeded to implement as many of the operators’ suggestions as possible in order to improve output as much as possible.


A few weeks after the changes, the cell was producing at its goal using at most two operators per shift. Additionally, the operators appreciated the changes, as they no longer reported having to work too hard. Working smarter not harder is a bit cliché, but it is definitely applicable in this situation.


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