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Data-Driven Function Network Analysis for Product Platform Planning: A Case Study of Spherical Rolling Robots

[+] Author Affiliations
Binyang Song, Jianxi Luo, Rajesh Elara Mohan, Kristin L. Wood

Singapore University of Technology and Design, Singapore, Singapore

Paper No. DETC2018-85759, pp. V007T06A040; 10 pages
doi:10.1115/DETC2018-85759
From:
  • ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 7: 30th International Conference on Design Theory and Methodology
  • Quebec City, Quebec, Canada, August 26–29, 2018
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5184-5
  • Copyright © 2018 by ASME

abstract

A properly designed product-system platform can reduce the cost and lead-time to design and develop a product family and thus achieve the tradeoff between economy of scope from product variety and economy of scale from platform sharing. Traditionally, product platform planning uses heuristic and manual approaches and relies on expertise and intuition. In this paper, we propose a data-driven method to draw the boundary of a platform, complementing other platform design approaches and assisting designers in the architecting process. The method generates a network of functions through relationships of their co-occurrences in prior designs of a product domain, and uses a network analysis algorithm to identify an optimal core-periphery structure. Functions identified in the network core co-occur cohesively and frequently with one another in prior designs, and thus are suggested for inclusion in the potential platform to be shared across a variety of product-systems with peripheral functions. We apply the method to identifying the platform functions for spherical rolling robots, based on patent data.

Copyright © 2018 by ASME

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