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Color Harmonization in Car Manufacturing Process

Author

Listed:
  • Anton Andriyashin
  • Michal Benko
  • Wolfgang Härdle
  • Roman Timofeev
  • Uwe Ziegenhagen

Abstract

One of the major cost factors in car manufacturing is the painting of body and other parts such as 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 colors 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 cooperation with a partner from car industry, combines classical tests and nonparametric 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 nonparametric smoothing. The aim of the analysis is to find a reliable technical solution which avoids any interaction from a human side.

Suggested Citation

  • Anton Andriyashin & Michal Benko & Wolfgang Härdle & Roman Timofeev & Uwe Ziegenhagen, 2006. "Color Harmonization in Car Manufacturing Process," SFB 649 Discussion Papers SFB649DP2006-071, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2006-071
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    File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2006-071.pdf
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    References listed on IDEAS

    as
    1. King, Eileen & Hart, Jeffrey D. & Wehrly, Thomas E., 1991. "Testing the equality of two regression curves using linear smoothers," Statistics & Probability Letters, Elsevier, vol. 12(3), pages 239-247, September.
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    Cited by:

    1. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
    2. Weining Wang & Ihtiyor Bobojonov & Wolfgang Karl Härdle & Martin Odening, 2011. "Increasing Weather Risk: Fact or Fiction?," SFB 649 Discussion Papers SFB649DP2011-077, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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    More about this item

    Keywords

    smoothing; resampling; nonparametric regression; trend detection;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other

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