Product concept generation and selection using sorting technique and fuzzy c-means algorithm

Wei Yan, Chun Hsien Chen, Meng Dar Shieh

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Product conceptualization is regarded as a key activity in new product development (NPD). In this stage, product concept generation and selection plays a crucial role. This paper presents a product concept generation and selection (PCGS) approach, which was proposed to assist product designers in generating and selecting design alternatives during the product conceptualization stage. In the PCGS, general sorting was adapted for initial requirements acquisition and platform definition; while a fuzzy c-means (FCM) algorithm was integrated with a design alternatives generation strategy for clustering design options and selecting preferred product concepts. The PCGS deliberates and embeds a psychology-originated method, i.e., sorting technique, to widen domain coverage and improve the effectiveness in initial platform formation. Furthermore, it successfully improves the FCM algorithm in such a way that more accurate clustering results can be obtained. A case study on a wood golf club design was used for illustrating the proposed approach. The results were promising and revealed the potential of the PCGS method.

Original languageEnglish
Pages (from-to)273-285
Number of pages13
JournalComputers and Industrial Engineering
Volume50
Issue number3
DOIs
Publication statusPublished - 2006 Jul

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Engineering(all)

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