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Optimum tolerance design using component-amount and mixture-amount experiments

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Abstract

The tolerance design problem involves optimizing component and assembly tolerances to minimize the total cost (sum of manufacturing cost and quality loss). Previous literature recommended using traditional response surface methodology (RSM) designs, models, and optimization techniques to solve the tolerance design problem for the worst-case scenario in which the assembly characteristic is the sum of the component characteristics. In this article, component-amount (CA) and mixture-amount (MA) experiment approaches are proposed as more appropriate for solving this class of tolerance design problems. The CA and MA approaches are typically used for product formulation problems, but can also be applied to this type of tolerance design problem. The advantages of the CA and MA approaches over the RSM approach and over the standard, worst-case tolerance-design method are explained. Reasons for choosing between the CA and MA approaches are also discussed. The CA and MA approaches (experimental design, response modeling, and optimization) are illustrated using real examples.

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Authors and Affiliations

  1. Applied Statistics and Computational Modeling, Pacific Northwest National Laboratory, Richland, WA, USA

    Greg F. Piepel

  2. Department of Econometrics, Faculty of Economics and Administrative Sciences Dokuz Eylul University, Buca, 35160, Izmir, Turkey

    Cenk Özler & Ali Kemal Şehirlioğlu

Authors
  1. Greg F. Piepel
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  2. Cenk Özler
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  3. Ali Kemal Şehirlioğlu
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Correspondence to Cenk Özler.

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Piepel, G.F., Özler, C. & Şehirlioğlu, A.K. Optimum tolerance design using component-amount and mixture-amount experiments. Int J Adv Manuf Technol 68, 2359–2369 (2013). https://doi.org/10.1007/s00170-013-4844-x

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  • DOI: https://doi.org/10.1007/s00170-013-4844-x

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