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A Weighted Set Cover Problem for Product Family Design to Maximize the Commonality of Products

Part of: Product Architecture and Modularization

Published online by Cambridge University Press:  26 July 2019

Hyeongmin Han ,
Sehyun Chang  and
Harrison Kim
Hyeongmin Han
Affiliation:
University of Illinois at Urbana-Champaign;
Sehyun Chang
Affiliation:
Hyundai Motor Company
Harrison Kim*
Affiliation:
University of Illinois at Urbana-Champaign;
*
Contact: Kim, Harrison, University of Illinois at Urbana-Champaign, Industrial and Enterprise Systems Engineering, United States of America, [email protected]

Abstract

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In product family design, the commonality of products and performance are competing objectives when designers build platforms. The commonality makes it efficient to manufacture products while it will cause performance loss of products. In this paper, we assume that performance functions evaluate the performance of a product. Targets of performance functions are set for each product depending on the product's property. The designs that satisfy the target of performance functions are denoted as ‘good’ design points. By using ‘good’ design points, a weighted set cover problem (WSC) is applied to formulate the combinatorial optimization problem, which maximizes the commonality by minimizing the number component attributes. A recursive greedy algorithm is proposed to handle the general cost function in the problem for product family design. The formulation and the algorithm are tested for a linear three-degree-of-freedom (3DOF) model. In numerical experiment, the proposed method determines optimal values of the components which are suspensions, stabilizer bars, and tires in the vehicle model.

Keywords

Product familiesPlatform strategiesOptimisation
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 2951 - 2960
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) 2019

References

Simpson, T.W., 2004, “Product platform design and customization: Status and promise”, Ai Edam, Vol. 18 No. 1, pp. 3–20.Google 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.Google Scholar
Du, X., Jiao, J. and Tseng, M.M., 2001, “Architecture of product family: fundamentals and methodology”, Concurrent Engineering, Vol. 9 No. 4, pp. 309–325.Google Scholar
Gonzalez-Zugasti, J.P., Otto, K.N. and Baker, J.D., 2000, “A method for architecting product platforms”, Research in engineering design, Vol. 12 No. 2, pp. 61–72.Google Scholar
Fujita, K. and Yoshida, H., 2004, “Product variety optimization simultaneously designing module combination and module attributes”, Concurrent Engineering, Vol. 12 No. 2, pp. 105–118.Google Scholar
Baylis, K., Zhang, G. and McAdams, D.A., 2018, “Product family platform selection using a Pareto front of maximum commonality and strategic modularity”, Research in Engineering Design, pp. 1–17.Google Scholar
Arciniegas, Rojas and Kim, A.J.H.M., 2011, “Optimal component sharing in a product family by simultaneous consideration of minimum description length and impact metric”, Engineering Optimization, Vol. 43 No. 2, pp. 175–192.10.1080/0305215X.2010.486032Google Scholar
Eichstetter, M., Müller, S. and Zimmermann, M., 2015, “Product family design with solution spaces”, Journal of Mechanical Design, Vol. 137 No. 12, p.121401.Google Scholar
Chvatal, V., 1979, “A greedy heuristic for the set-covering problem”, Mathematics of operations research, Vol. 4 No. 3, pp. 233–235.10.1287/moor.4.3.233Google Scholar
Peng, H., 1996. Lecture Notes for ME542: Vehicle Dynamics. Mechanical Engineering Department, University of Michigan.Google Scholar
Lei, N. and Moon, S.K., 2015, “A Decision Support System for market-driven product positioning and design”, Decision Support Systems, Vol. 69, pp. 82–91.10.1016/j.dss.2014.11.010Google Scholar
Rai, R. and Allada, V., 2003, “Modular product family design: agent-based Pareto-optimization and quality loss function-based post-optimal analysis”, International Journal of Production Research, Vol. 41 No. 17, pp. 4075–4098.Google 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. 119–129.10.1177/1063293X04044383Google Scholar
Khajavirad, A., Michalek, J.J. and Simpson, T.W., 2009, “An efficient decomposed multiobjective genetic algorithm for solving the joint product platform selection and product family design problem with generalized commonality”, Structural and Multidisciplinary Optimization, Vol. 39 No. 2, pp. 187–201.Google 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.101004.Google Scholar
Nelson, S.A., Parkinson, M.B. and Papalambros, P.Y., 2001, “Multicriteria optimization in product platform design”, Journal of Mechanical Design, Vol. 123 No. 2, pp. 199–204.Google Scholar