Optimisation of multiple responses using a fuzzy rule-based inference system

D. Lu, J. Antony

Research output: Contribution to journalArticle

55 Citations (Scopus)

Abstract

The optimization of multiple responses (or performance characteristics) has received increasing attention over the last few years in many manufacturing organizations. Many Taguchi practitioners have employed past experience and engineering knowledge or judgement when dealing with multiple responses. This approach brings an element of uncertainty to the decision-making process and therefore is not recommended for optimization of multiple responses. The approach presented in this paper takes advantage of both the Taguchi method and a fuzzy-rule based inference system, which forms a robust and practical methodology in tackling multiple response optimization problems. The paper also presents a case study to illustrate the potential of this powerful integrated approach for tackling multiple response optimization problems. The variance analysis is also an integral part of the study, which identifies the most critical and statistically significant parameters.
LanguageEnglish
Pages1613-1625
Number of pages12
JournalInternational Journal of Production Research
Volume40
Issue number7
DOIs
Publication statusPublished - 2002

Fingerprint

Fuzzy rules
Knowledge engineering
Taguchi methods
Decision making
Rule-based
Inference
Optimization problem

Keywords

  • logistics
  • manufacturing engineering
  • manufacturing industries
  • manufacturing technology
  • operations management
  • quality control management
  • production research
  • production systems

Cite this

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Optimisation of multiple responses using a fuzzy rule-based inference system. / Lu, D.; Antony, J.

In: International Journal of Production Research, Vol. 40, No. 7, 2002, p. 1613-1625.

Research output: Contribution to journalArticle

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