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

Pramote Charongrattanasakul | Zendy; Adisak Pongpullponsak | Zendy

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

Author(s) -

Pramote Charongrattanasakul,

Adisak Pongpullponsak

Publication year - 2017

Publication title -

engineering journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.246

H-Index - 20

ISSN - 0125-8281

DOI - 10.4186/ej.2017.21.2.253

Subject(s) - weibull distribution , genetic algorithm , fuzzy logic , computer science , algorithm , reliability engineering , mathematics , mathematical optimization , statistics , engineering , artificial intelligence

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 ( , , , , , ) n h L k w that minimize the fuzzy hourly cost. Finally, the fuzzy hourly cost is transformed to crisp number by the centroid defuzzification.

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