The COVID-19 pandemic and its distancing made teaching quite difficult. On-site trainings on the shop floor especially were no longer possible. Torbjørn Netland, Head of Chair of Production and Operations Management (POM) at ETH Zurich took this challenge as an opportunity and brought the factory to the students virtually. Let me show you his success.
To become lean, you need to improve your factory. Continuous improvement (kaizen) consists of many smaller and/or larger improvements. However, often the first challenge is where to start this improvement. Let me dig deeper into the possibilities and challenges of picking improvement projects, with a particular focus on systems that have multiple independent production lines, which makes everything trickier.
Screws, or more generally fasteners, are a main staple in most industries. Recently I visited a factory and saw a nice way to automate the procurement of screws and other fasteners. This Industry 4.0 solution is part of a vendor-managed inventory (VMI), where you not only buy the screw, but also the service of always having enough screws, and let the vendor manage the hassle of making sure there are enough screws. I found the example in this factory quite neat, and hence decided to tell you about it. Let me show you.
In my last post I started to look at the difficulties of handling data in Industry 4.0. I looked especially at the complexity and the often underestimated problem of merging data from different sources or machines. This second post of this two-post series finishes up this topic and will look at the also important and often underestimated task of cleaning up the data.
Industry 4.0 is still a hot topic, even over ten years after the term was coined. Unfortunately, very often I find it to be much more hype than content. The examples where it actually worked well are few and far between, and the examples where not much was hyped as groundbreaking are way too frequent. In my view, a large problem of Industry 4.0 is the data, especially the data structure and the problems with analyzing the data. Hence, (yet another) short series of post warning on the difficulties of Industry 4.0 with a focus on the data.
Toyota did not start out as a lean company, but evolved over time. This was also not an automatic process. It needed a lot of care and attention, as well as continuous improvement and PDCA. This is the second post of this short, two-post series on the path of Toyota from a messy and hard-to-manage job shop to a much more efficient flow shop.
When setting up a new production – or even when rearranging an existing production – one important decision is how to arrange your processes. I have written a lot on line layout, but this post will look at how the arrangement of lines evolved at Toyota. Some of their insights are now accepted wisdoms in lean, but many companies still struggle with it. This post also looks into the manning of machines, especially multi-machine handling. The blog post is based on the appendix in the Toyota Handbook from 1973.