Real vs. Planned Data in Pull Systems

Pull systems like kanban and reorder point are a cornerstone of inventory management and fluctuation reduction in lean manufacturing. The production is managed based on ACTUAL consumption. Theoretically, it is also possible to include expected but not yet actual consumption. In this post, I will explain to you the concept behind it and why I think it is a bad idea…

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How to Reduce Part Variants

In my last post I looked at how to reduce product variants, and the inevitable conflict with sales. In this post I will look at how to reduce not the number of final products, but the number of part types that go into the final product… and here you often have a conflict with product development. However, like the reduction of the number of final products, this reduction in fluctuation has significant benefits for the company.

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How to Reduce Product Variants

Steering wheelsProduct variants drive up cost. The more variants you have for the same quantity sold, the higher your production cost. Inversely, if you can reduce your number of variants, you can reduce your cost. In this post I will give you some general suggestions on how to reduce your number of variants. Hopefully these inspire and help you to become more efficient.

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Make-to-Order vs Make-to-Stock: Additional Decision Factors

For all your products, you have to decide between make-to-order and make-to-stock. A similar decision is needed for components or raw materials that you produce or purchase. As described in my precious posts, the key criteria is the quantity and the fluctuation. In this last post in this small series I will look at where to make the cut, and what other factory play a secondary role for your production system.

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Make-to-Order vs Make-to-Stock: The ABC XYZ Analysis

In my last post I started to look at when to produce make-to-stock and when to produce make-to-order. There are quite a few factors that influence this decision (more on this in my next post), but the most important ones are the total sales or production volume as well as the fluctuations thereof. To understand these, you could use a Pareto analysis, an ABC analysis, or an ABC-XYZ analysis. I do like to include not only quantity but also fluctuations, but usually I need to divide this into only two groups, and the three groups of ABC or nine groups of ABC-XYZ is, in my view, a bit of an overkill. Anyway, let’s have a look:

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When to Produce Make-to-Order, When Make-to-Stock?

One of the questions for any production system is if the product is produced on stock before the customer order (make-to-stock, MTS), or only on demand after the customer order (make-to-order, MTO). In many cases this is an easy decision. Custom-made items are always make-to-order, since you cannot start before you know what the product will be. Everything else does have exceptions. Let me dig deeper into the decision tree on deciding which items to produce on order, and which ones for stock. This is a short series of blog posts, and the first one looks at the key aspect (but not the only one) in deciding between make-to-order and make-to-stock.

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Can You Plan Around Your Fluctuations?

Abstract Wave MoleculeBalancing the need of high material availability with low inventory is tricky. Pull systems are a very good way to achieve this. But sometimes people argue with me that planning can be better if you use all the available information to create a production plan which then outperforms a pull system. In theory, this could work, but in practice it rarely does. After all, that is what conventional push systems are trying to achieve, usually with mediocre results. Let’s have a look.

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About Just in Time and Fluctuations (Like… a Pandemic…)

Global logistics networkJust in Time (JIT) is a powerful tool in lean. However, it is not an easy tool. Using it without understanding the requirements can quickly make things worse. I have written about related topics before, but during the COVID-19 pandemic, Just in Time was often blamed for a lack of material, usually by people who do not understand how just in time works.

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