Genetic algorithms and fuzzy systems in process planning and scheduling for an agile manufacturing system / Yousef Mohammad Karimi in International journal of management science and engineering management, Vol. 5 N° 1 (Fevrier 2010)  

Public ISBD [article]  inInternational journal of management science and engineering management > Vol. 5 N° 1 (Fevrier 2010) . - pp.65-71 Titre : Genetic algorithms and fuzzy systems in process planning and scheduling for an agile manufacturing system Type de document : texte imprimé Auteurs : Yousef Mohammad Karimi, Auteur Année de publication : 2011 Article en page(s) : pp.65-71 Note générale : Management Langues : Anglais (eng) Mots-clés : Genetic algorithms Fuzzy inference system Agile manufacturing Process planning and scheduling Résumé : This paper proposes an integrated Genetic Algorithms and Fuzzy Systems method in choosing alternative machines for process planning and scheduling of an Agile manufacturing system. A case study carried out in an agile company based in the production of automobile parts. Instead of choosing alternative machines randomly, machines are being selected based on the machines reliability. The MTTF values are input in a fuzzy inference mechanism, which outputs the machine reliability. The machine is then being penalized based on the fuzzy output. The most reliable machine will have the higher priority to be chosen. In order to overcome the problem of un-utilization machines, sometimes faced by unreliable machine, the Genetic Algorithms have been used to balance the load for all the machines. Some Results shows in integrating production capability and load balancing during scheduling activity. DEWEY : 658 ISSN : 1750-9653 En ligne : http://www.ijmsem.org/OnlineJournal.do/?116.html [article] Genetic algorithms and fuzzy systems in process planning and scheduling for an agile manufacturing system [texte imprimé] / Yousef Mohammad Karimi, Auteur . - 2011 . - pp.65-71. Management Langues : Anglais (eng) in International journal of management science and engineering management > Vol. 5 N° 1 (Fevrier 2010) . - pp.65-71 Mots-clés : Genetic algorithms Fuzzy inference system Agile manufacturing Process planning and scheduling Résumé : This paper proposes an integrated Genetic Algorithms and Fuzzy Systems method in choosing alternative machines for process planning and scheduling of an Agile manufacturing system. A case study carried out in an agile company based in the production of automobile parts. Instead of choosing alternative machines randomly, machines are being selected based on the machines reliability. The MTTF values are input in a fuzzy inference mechanism, which outputs the machine reliability. The machine is then being penalized based on the fuzzy output. The most reliable machine will have the higher priority to be chosen. In order to overcome the problem of un-utilization machines, sometimes faced by unreliable machine, the Genetic Algorithms have been used to balance the load for all the machines. Some Results shows in integrating production capability and load balancing during scheduling activity. DEWEY : 658 ISSN : 1750-9653 En ligne : http://www.ijmsem.org/OnlineJournal.do/?116.html

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