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Research Papers: Design Theory and Methodology

Data-Driven Platform Design: Patent Data and Function Network Analysis

[+] Author and Article Information
Binyang Song

Engineering Product Development,
Singapore University of Technology and Design,
8 Somapah Road,
Singapore 487372
e-mail: Binyang_song@mymail.sutd.edu.sg

Jianxi Luo

Engineering Product Development,
Singapore University of Technology and Design,
8 Somapah Road,
Singapore 487372;
International Design Center,
Singapore University of Technology and Design,
8 Somapah Road,
Singapore 487372
e-mail: jianxi_luo@sutd.edu.sg

Kristin Wood

Engineering Product Development,
Singapore University of Technology and Design,
8 Somapah Road,
Singapore 487372;
International Design Center,
Singapore University of Technology and Design,
8 Somapah Road,
Singapore 487372
e-mail: kristinwood@sutd.edu.sg

1Corresponding author.

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received June 28, 2018; final manuscript received November 15, 2018; published online December 20, 2018. Assoc. Editor: Carolyn Seepersad.

J. Mech. Des 141(2), 021101 (Dec 20, 2018) (10 pages) Paper No: MD-18-1499; doi: 10.1115/1.4042083 History: Received June 28, 2018; Revised November 15, 2018

A properly designed product-system platform seeks to reduce the cost and lead time for design and development of the product-system family. A key goal is to achieve a 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 almost solely on expertise and intuition. In this paper, we propose a data-driven method to draw the boundary of a platform-system, complementing the 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 or systems 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 identify the platform functions for the application domain of spherical rolling robots (SRRs), based on patent data.

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Figures

Grahic Jump Location
Fig. 1

Structures of various types of core–periphery networks: (a) Typical core-periphery, (b) Rich-clubs, (c) Nested, (d) Bow-tie, and (e) Onion

Grahic Jump Location
Fig. 2

(a)–(c) The spherical rolling robot product family from Sphero, Inc., and (d) Virgo from SUTD: (a) Sphero, (b) BB-8, (c) BB-9E, and (d) Virgo

Grahic Jump Location
Fig. 3

The co-occurrence network of functions identified in prior SRR designs. Core functions are highlighted as solids and peripheral functions are represented as circles.

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