Design and implementation of a fuzzy inference system for supporting customer requirements

Ying Shen Juang, Shui Shun Lin, Hsing Pei Kao

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Efficient and effective response to the requirements of customers is a major performance indicator. Failure to satisfy customer requirements implies operational weaknesses in a company. These weaknesses will damage both the rights of customers and the reputation of the company. The traditional method of handling customer requirement for a machine tool manufacturer was dominated by manual process and subjective decision. In this study, we improved the operation process of handling customer requirement. The framework of a customer requirement information system (CRIS) for machine tool manufacturers was then analyzed, integrating rule-based fuzzy inference and expert systems, and a prototype system developed. The CRIS supports both customers and service personnel in providing a systematic way of fulfilling and analyzing customer requirements. The system was installed and operated in a machine tool manufacturer and the performance was found promising.

Original languageEnglish
Pages (from-to)868-878
Number of pages11
JournalExpert Systems with Applications
Volume32
Issue number3
DOIs
StatePublished - Apr 2007

Keywords

  • Customer requirements
  • Expert systems
  • Fault diagnosis
  • Fuzzy inference
  • Integrated information system

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