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Optimization of multiple responses using a fuzzy-rule based inference system
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Lu, Dawei and Antony, Jiju (2002) Optimization of multiple responses using a fuzzy-rule based inference system. International Journal of Production Research , Vol. 40 (No. 7). pp. 1613-1625. doi:10.1080/00207540210122202
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Official URL: http://dx.doi.org/10.1080/00207540210122202
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.
| Item Type: | Journal Article | ||||
|---|---|---|---|---|---|
| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management T Technology > TS Manufactures |
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| Divisions: | Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) | ||||
| Library of Congress Subject Headings (LCSH): | Taguchi methods (Quality control), Fuzzy logic | ||||
| Journal or Publication Title: | International Journal of Production Research | ||||
| Publisher: | Taylor & Francis Ltd. | ||||
| ISSN: | 0020-7543 | ||||
| Official Date: | May 2002 | ||||
| Dates: |
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| Volume: | Vol. 40 | ||||
| Number: | No. 7 | ||||
| Number of Pages: | 13 | ||||
| Page Range: | pp. 1613-1625 | ||||
| DOI: | 10.1080/00207540210122202 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access |
Data sourced from Thomson Reuters' Web of Knowledge
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