Abstract
The research performed in this work is based on four case studies. Their purpose is to confirm the model, find its limitations, and show opportunities for future research. The case studies are combined with action research as the situation in every case is optimized and the effect of the action taken is assessed. The cases apply the complexity management model presented in the previous chapter to four different products:
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Railroad signal;
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Liquid handling platform;
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Process industry compressor;
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Railroad switch lock.
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References
As cited in Mayer (1993, p. 35)
An ABC analysis as used here classifies every product variant with regard to its importance relative to all variants of a product. The importance can be measured by units sold, sales dollars, manufacturing costs, etc. In Figure 5.1, the fraction of sales volume is used. Frequently, it can be observed that a small number of products (or product variants) generate a large portion of sales (Schönsleben, 2002, p. 459). This is often associated with the Pareto principle (or the 80-20 rule), which states that 80 percent of activities or consequences are due to 20 percent of the causes. The classification of A, B, and C products (or product variants) does not follow a strict rule; often, A products are defined as the top 20 percent, and B products the next 30 to 40 percent, and C products the rest.
According to Tanaka (1989, p. 67), for components outside the optimal value zone (to the left of the zone in Figure 5.21), “cost increases may be necessary to ensure that the product performs its functions satisfactorily.” Cost increases do not always make sense, but the potential should be investigated nevertheless. Therefore, the upper left portion of the value control chart in Figure 5.21 is labeled “check whether under-engineered.”
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© 2007 Deutscher Universitäts-Verlag | GWV Fachverlage GmbH, Wiesbaden
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(2007). Case Studies. In: Complexity Management. DUV. https://doi.org/10.1007/978-3-8350-5435-6_5
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