Requirement analysis considering uncertain customer preference for Kansei quality of product

Kazuko Yamagishi, Kenichi Seki, Hidekazu Nishimura

Research output: Contribution to journalArticle

Abstract

This paper proposes a requirement analysis approach to increase the robustness of the Kansei quality and maximise customer satisfaction for consumer electronics products. Recently, the importance of the Kansei quality such as comfort and luxury is increasing to enhance value of the product. The Kansei quality of the target product must be assessed through individual customer’s sensitivity, which will discern their preference. The customer preference has inherent uncertainties that depend on personal value. The way of reducing the influence of customer preference diversity for the Kansei quality is desired. First, to capture comprehensively the uncertainties of customer preference for Kansei quality, customer preference is evaluated by a preference evaluation test and cluster analysis. The customer preference clusters resulting from this analysis reveal the preference patterns and their frequencies. To investigate thoroughly requirements including Kansei quality for the product, the evaluation grid method is carried out for each customer preference cluster. Next, to select appropriate design factors, which strongly influence the customer preference in each cluster, multiple regression analysis for them is conducted with preference evaluation test result. Finally, by multiple-domain matrix-based expressions using multiple regression analysis, customer preference, Kansei quality, and physical design are connected with complete coverage. Using this MDM, even in complex product designs, designers can find satisfactory solutions certainly.

Original languageEnglish
JournalJournal of Advanced Mechanical Design, Systems and Manufacturing
Volume10
Issue number2
DOIs
Publication statusPublished - 2016 Jan 1

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Keywords

  • Customer preference
  • Evaluation grid method
  • Kansei quality
  • Multiple-domain matrix (MDM)
  • Uncertainties

ASJC Scopus subject areas

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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