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Identification of Product Family Platforms Using Pattern Recognition

[+] Author Affiliations
Dane Freeman, Dongwook Lim, Elena Garcia, Dimitri Mavris

Georgia Institute of Technology, Atlanta, GA

Paper No. DETC2011-47472, pp. 1027-1039; 13 pages
doi:10.1115/DETC2011-47472
From:
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5: 37th Design Automation Conference, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5482-2
  • Copyright © 2011 by ASME

abstract

In product family design the goal is to generate a set of lowest cost products that target specific market niches. Sharing components, called platforms, between different products can minimize duplication of effort, thereby lowering family costs. However, if the products’ requirements are too dissimilar, sharing components may compromise the end product; such variance will lead to lower end products being overdesigned and/or higher end products being underdesigned. It is important to identify which components are similar enough, so that sharing does not compromise the individual products’ performances. Most existing product family design methods make decisions a priori about platforms; constraining platforms to be used by every product in the family, or not at all. Methods that simultaneously optimize component sharing and design variable settings have the potential to find better families because product subsets may be more similar to each other than to other subsets of products. Allowing components to be shared between any subset of family members leads to a very large combinatorial problem, and considering large product families can be computationally prohibitive. This paper proposes a method to identify possible sets of product family platforms by using the pattern recognition technique of fuzzy c-means clustering on component subspaces. Component subspaces are taken from a database of generated design points for the whole family. If components from different products are similar enough to be grouped into the same cluster, then those components could possibly become the same platform. Fuzzy equivalence relations can be extracted from the cluster membership functions that show the binary relationship from one products’ component to a different products’ component. Ultimately, this method can be used as a platform identification heuristic in a larger product family design methodology. This method is demonstrated by applying it to find possible common components in a family of universal electric motors.

Copyright © 2011 by ASME

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