Hostname: page-component-6bf8c574d5-gr6zb Total loading time: 0 Render date: 2025-02-16T20:49:49.292Z Has data issue: false hasContentIssue false
  • English
  • Français

COST OPTIMIZATION OF PRODUCT FAMILIES USING SOLUTION SPACES

Part of: Design Methods

Published online by Cambridge University Press:  11 June 2020

S. Rötzer ,
D. Thoma  and
M. Zimmermann
S. Rötzer*
Affiliation:
Technical University of Munich, Germany
D. Thoma
Affiliation:
ID-Consult GmbH, Germany
M. Zimmermann
Affiliation:
Technical University of Munich, Germany
*
*[email protected]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Maximizing the number of shared components does not always produce cost-optimal product families. Shared components can yield economies of scale due to reuse of components, but also increases material cost due to over dimensioning. In this paper, we present an approach to identify a cost-optimal design for product families. It consists of two steps: (1) identifying a scheme to share components in the product family and (2) finding the cost optimal design for the product family.

Keywords

complex systemssystems engineering (SE)cost optimisationsolution space engineeringproduct families
Type
Article
Information
Proceedings of the Design Society: DESIGN Conference , Volume 1 , May 2020 , pp. 1087 - 1094
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2020. Published by Cambridge University Press

References

Chowdhury, S., Messac, A. and Khire, R. (2010), “Developing a Non-gradient Based Mixed-Discrete Optimization Approach for Comprehensive Product Platform Planning (CP3)”, In 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference, Fort Worth, Texas, American Institute of Aeronautics and Astronautics, Reston, Virigina, p. 583. https://doi.org/10.2514/6.2010-9174CrossRefGoogle Scholar
Chowdhury, S., Messac, A. and Khire, R.A. (2011), “Comprehensive Product Platform Planning (CP3) Framework”, Journal of Mechanical Design, Vol. 133 No. 10, p. 294. https://doi.org/10.1115/1.4004969CrossRefGoogle Scholar
Eichstetter, M., Müller, S. and Zimmermann, M. (2015), “Product Family Design With Solution Spaces”, Journal of Mechanical Design, Vol. 137 No. 12, https://doi.org/10.1115/1.4031637CrossRefGoogle Scholar
Fellini, R. et al. (2004), “A sensitivity-based commonality strategy for family products of mild variation, with application to automotive body structures”, Structural and Multidisciplinary Optimization, Vol. 27 No. 1-2, pp. 89–96. https://doi.org/10.2514/6.2002-5610CrossRefGoogle Scholar
Henderson, B. (1973), “The Experience Curve. Reviewed (Part II)”.Google Scholar
Khajavirad, A. and Michalek, J.J. (2008), “A Decomposed Gradient-Based Approach for Generalized Platform Selection and Variant Design in Product Family Optimization”, Structural and Multidisciplinary Optimization, Vol. 130 No. 7, pp. 1–8. https://doi.org/10.1115/1.2918906Google Scholar
Simpson, T.W. (2004), “Product platform design and customization: Status and promise”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 18 No. 1, pp. 3–20. https://doi.org/10.1017/s0890060404040028CrossRefGoogle Scholar
Simpson, T.W. (2006), “Methods for Optimizing Product Platforms and Product Families”, In: Simpson, T.W., Siddique, Z. and Jiao, J. (Eds.), Product platform and product family design: Methods and applications, Springer, New York. https://doi.org/10.1007/0-387-29197-0_8CrossRefGoogle Scholar
Simpson, T.W. and D'Souza, B.S. (2004), “Assessing Variable Levels of Platform Commonality Within a Product Family Using a Multiobjective Genetic Algorithm”, Concurrent Engineering, Vol. 12 No. 2, pp. 119–129. https://doi.org/10.1177/1063293x04044383CrossRefGoogle Scholar
Simpson, T.W., Maier, J.R. and Mistree, F. (2001), “Product platform design: method and application”, Research in Engineering Design, Vol. 13 No. 1, pp. 2–22. https://doi.org/10.1007/s001630100002CrossRefGoogle Scholar
Skirde, H., Kersten, W. and Möller, K. (2015), Kostenorientierte Bewertung modularer Produktarchitekturen, Zugl.: Hamburg-Harburg, Techn. Univ., Institut für Logistik und Unternehmensführung, Diss., 2015, Reihe, Vol. 20 No. 1. Aufl., Eul, Lohmar.Google Scholar
Zapico, M. et al. (2015), “Towards product platform introduction: optimising commonality of components”, in Weber, C., Husung, S., Cascini, G., Cantamessa, M. and Marjanović, D. (Eds.), The 20th International Conference on Engineering Design (ICED15): 27th-30th July 2015, Politecnico di Milano, Italy proceedings of ICED15, Design Society, Glasgow, Scotland.Google Scholar
Zimmermann, M. et al. (2017), “On the design of large systems subject to uncertainty”, Journal of Engineering Design, Vol. 28 No. 4, pp. 233–254. https://doi.org/10.1080/09544828.2017.1303664CrossRefGoogle Scholar