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Key Characteristics identification by global sensitivity analysis

  • Dana IdrissEmail author
  • Pierre Beaurepaire
  • Lazhar Homri
  • Nicolas Gayton
Original Paper
  • 7 Downloads

Abstract

During the design stage of product manufacturing, the designers try to specify only the necessary critical dimensions or what is called “Key Characteristics”. Knowing that dealing with Key Characteristics is time consuming and costly, it is preferable to reduce their number and exclude the non-contributing parameters. Different strategies that are based on qualitative or quantitative approaches for the identification of these dimensions are followed by the companies. The common way is to define the critical functional requirements which are expressed in terms of dimensions. When the functional requirements are set as critical, all the involved dimensions are labelled as Key Characteristics. However they do not have the same importance and need to be classified between contributing and non-contributing parameters. There is not a quantitative method that serves for the identification of Key Characteristics in the critical functional requirements. This paper suggests a numerical methodology which can be a step forward to a better ranking of the Key Characteristics. It is based on the global sensitivity analysis and more precisely on Sobol’ approach. The sensitivity of the Non Conformity Rate corresponding to the production of the product is measured with respect to the variable parameters characterizing the dimensions. The method is applied, first on a simple two-part example, then on a system having a linearised functional requirement and finally on a system with two non-linear functional requirements. The results show the main effects of the dimensions in addition to their interactions. Consequently it is possible to prioritize some and neglect the effect of the others and classify them respectively as Key Characteristics or not.

Keywords

Key Characteristics Tolerance Analysis Global Sensitivity Analysis Sobol’ indices 

Notes

Acknowledgements

The authors would like to acknowledge the Fonds Unique Interministriel for funding this work and the partners of AHTOLAnd project for their helpful comments and support. They are also grateful to Jean Yves Dantan, from ENSAM Metz, Laurent Gauvrit, from RADIALL, Sebastien Jallet, Lionel Cros and Pascal Vacher, from Valeo WS, Pierre-Alain Rance, from Mecamaster, for their helpful discussions and comments.

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Copyright information

© Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  • Dana Idriss
    • 1
    Email author
  • Pierre Beaurepaire
    • 1
  • Lazhar Homri
    • 2
  • Nicolas Gayton
    • 1
  1. 1.CNRS, SIGMA Clermont, Institut PascalUniversité Clermont AuvergneClermontFerrandFrance
  2. 2.LCFC, Arts et Mtiers ParisTech, ENSAMUniversité de LorraineMetz Cedex 3France

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