Optimizing the Cost of Integrated Model for Fuzzy Failure Weibull Distribution Using Genetic Algorithm

  • Pramote Charongrattanasakul King Mongkut's University of Technology Thonburi
  • Adisak Pongpullponsak King Mongkut's University of Technology Thonburi

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Abstract

This research applies the fuzzy concept in development of an integrated model (Statistical process control and Maintenance management) with Weibull distribution for Exponentially Weighted Moving Average (EWMA) control chart. Since sample data may contain uncertainties coming from measurement systems and environment conditions, fuzzy number is used to inspect these suspicions. Moreover, the Weibull distribution with fuzzy scale parameters is considers, and the genetic algorithm approach is used to determine the optimal values of six variables that minimize the fuzzy hourly cost. Finally, the fuzzy hourly cost is transformed to crisp number by the centroid defuzzification.

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Author Biographies
Pramote Charongrattanasakul

Department of Mathematics, Faculty of Science, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand

Adisak Pongpullponsak

Department of Mathematics, Faculty of Science, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand

Published
Vol 21 No 2, Mar 31, 2017
How to Cite
P. Charongrattanasakul and A. Pongpullponsak, “Optimizing the Cost of Integrated Model for Fuzzy Failure Weibull Distribution Using Genetic Algorithm”, Engineering Journal (Eng. J.), vol. 21, no. 2, pp. 253-268, Mar. 2017.

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