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Comprehensive Product Platform Planning (CP3) Using Mixed-Discrete Particle Swarm Optimization and a New Commonality Index

[+] Author Affiliations
Souma Chowdhury

Rensselaer Polytechnic Institute, Troy, NY

Achille Messac

Syracuse University, Syracuse, NY

Ritesh Khire

United Technologies Research Center (UTRC), East Hartford, CT

Paper No. DETC2012-70954, pp. 983-999; 17 pages
  • ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 3: 38th Design Automation Conference, Parts A and B
  • Chicago, Illinois, USA, August 12–15, 2012
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-4502-8
  • Copyright © 2012 by ASME


A product family with a common platform paradigm can increase the flexibility and responsiveness of the product-manufacturing process and help take away market share from competitors that develop one product at a time. The recently developed Comprehensive Product Platform Planning (CP3) method allows (i) the formation of sub-families of products, and (ii) the simultaneous identification and quantification of platform/scaling design variables. The CP3 model is founded on a generalized commonality matrix representation of the product-platform-plan. In this paper, a new commonality index is developed and introduced in CP3 to simultaneously account for the degree of inter-product commonalities and for the overlap between groups of products sharing different platform variables. To maximize both the performance of the product family and the new commonality measure, we develop and apply an advanced mixed-discrete Particle Swarm Optimization (MDPSO) algorithm. In the MDPSO algorithm, the discrete variables are updated using a deterministic nearest-feasible-vertex criterion after each iteration of the conventional PSO. Such an approach is expected to avoid the undesirable discrepancy in the rate of evolution of discrete and continuous variables. To prevent a premature stagnation of solutions (likely in conventional PSO), while solving the high dimensional MINLP problem presented by CP3, we introduce a new adaptive diversity-preservation technique. This technique first characterizes the population diversity and then applies a stochastic update of the discrete variables based on the estimated diversity measure. The potential of the new CP3 optimization methodology is illustrated through its application to design a family of universal electric motors. The optimized platform plans provide helpful insights into the importance of accounting for the overlap between different product platforms, when quantifying the effective commonality in the product family.

Copyright © 2012 by ASME



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