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Proposal for tool-based method of product cost estimation during conceptual design

Author

Listed:
  • Magali Mauchand

    (IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes - Mines Nantes - Mines Nantes - ECN - École Centrale de Nantes - EPUN - Ecole Polytechnique de l'Université de Nantes - UN - Université de Nantes - UNAM - PRES Université Nantes Angers Le Mans - CNRS - Centre National de la Recherche Scientifique)

  • Ali Siadat
  • Alain Bernard

    (IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes - Mines Nantes - Mines Nantes - ECN - École Centrale de Nantes - EPUN - Ecole Polytechnique de l'Université de Nantes - UN - Université de Nantes - UNAM - PRES Université Nantes Angers Le Mans - CNRS - Centre National de la Recherche Scientifique)

  • Nicolas Perry

    (LGM2B - Laboratoire Génie Mécanique et Matériaux de Bordeaux - UB - Université Sciences et Technologies - Bordeaux 1)

Abstract

The undertaken project aims at offering a support for the manufacturing cost estimation of products in the conceptual design phase. This need for dedicated tools for designers emerges from the lack of means to determinate the best technical solution that permits one to save costs and to reach safe quality. The main objective of this tool is to assist the designer in the process of manufacturing cost calculation of a product that is defined by little and inaccurate information in the preliminary design. This paper presents a procedure to develop such a tool.

Suggested Citation

  • Magali Mauchand & Ali Siadat & Alain Bernard & Nicolas Perry, 2008. "Proposal for tool-based method of product cost estimation during conceptual design," Post-Print hal-00476631, HAL.
    • Handle: RePEc:hal:journl:hal-00476631
    DOI: 10.1080/09544820701802857
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    Cited by:

    1. Zbigniew Leszczyński & Tomasz Jasiński, 2020. "Comparison of Product Life Cycle Cost Estimating Models Based on Neural Networks and Parametric Techniques—A Case Study for Induction Motors," Sustainability, MDPI, vol. 12(20), pages 1-14, October.
    2. Antonio Armillotta, 2021. "On the role of complexity in machining time estimation," Journal of Intelligent Manufacturing, Springer, vol. 32(8), pages 2281-2299, December.

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