In my last two posts I talked on how to set up a changeover wheel or, more generally, a changeover sequence. Next I will show you how to use a changeover wheel. The idea is simple, but there are some pitfalls as well as some tricks to make it easier. Let’s have a look.
In my last post of this series on the changeover wheel and changeover sequencing, I showed you the basics on how to use a changeover wheel or changeover sequence. In this post I will look at a few options and modifications that are sometimes used too.
In my last posts I talked on how to set up a changeover wheel or, more generally, a changeover sequence. Next I will show you how to use a changeover wheel. You have to fit you prioritized production into the sequence. The idea is simple, but there are some pitfalls as well as some tricks to make it easier. I will talk more about the pitfalls in my next post. Let’s have a look on how to fill the changeover wheel with actual production jobs.
In my last post I looked at how to create a changeover sequence. However, this was only the first draft of such a sequence. For a truly good sequence, you need to spend some more time optimizing the sequence. Try to get a better sequence, even though it is impossible to find the perfect solution even for a moderate number of products. I also give a suggestion on how to visualize a changeover wheel in Excel.
The changeover wheel is a visualization of a good changeover sequence. In this series of posts I will go deeper on how to use such a changeover sequence in planning your production sequence. The concept itself is simple, but there are still some pitfalls in using it. This first post looks deeper at generating a first sequence. My next post will then optimize the sequence, where we will also learn why you probably should not shoot for the perfect solution, but merely for good enough.
There is a big hype on anything related to computers in manufacturing. I have written quite a few cautionary articles on the Industry 4.0 bandwagon. This post looks more in-depth into artificial intelligence (AI). I believe there are possible applications of AI in manufacturing, but at the moment these are still uncommon. In this post I would like to talk a bit about the hype, but also present a few examples of where it actually works. Let me show you:
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.