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One of the major cost factors in car manufacturing is the painting of the body and other parts such as the wing or bonnet. Surprisingly, the painting may be even more expensive than the body itself. From this point of view it is clear that car manufacturers need to observe the painting process carefully to avoid any deviations from the desired result. Especially for metallic colours where the shining is based on microscopic aluminium particles, customers tend to be very sensitive towards a difference in the light reflection of different parts of the car. The following study, carried out in close co‐operation with a partner from car industry, combines classical tests and non‐parametric smoothing techniques to detect trends in the process of car painting. The localized versions motivated by t‐test, Mann–Kendall, Cox–Stuart and a change point test are employed in this study. Suitable parameter settings and the properties of the proposed tests are studied by simulations based on resampling methods borrowed from non‐parametric smoothing. The aim of the analysis is to find a reliable technical solution which avoids any interaction from the human side. Copyright © 2006 John Wiley & Sons, Ltd.
Applied Stochastic Models in Business and Industry – Wiley
Published: Sep 1, 2006
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