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Classification analysis for simulation of the duration of machine breakdowns / Lu, L. in Journal of the operational research society (JORS), Vol. 62 N° 4 (Avril 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 4 (Avril 2011) . - pp. 760–767 Titre : Classification analysis for simulation of the duration of machine breakdowns Type de document : texte imprimé Auteurs : Lu, L., Auteur ; Currie, C. S. M., Auteur ; Cheng, R. C. H., Auteur Année de publication : 2011 Article en page(s) : pp. 760–767 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Simulation  Classification  Manufacturing  Bootstrapping Index. décimale : 001.424 Résumé : Machine failure can have a significant impact on the throughput of manufacturing systems, therefore accurate modelling of breakdowns in manufacturing simulation models is essential. Finite mixture distributions have been successfully used by Ford Motor Company to model machine breakdown durations in simulation models of engine assembly lines. These models can be very complex, with a large number of machines. To simplify the modelling we propose a method of grouping machines with similar distributions of breakdown durations, which we call the Arrows Classification Method, where the Two-Sample Cramér-von-Mises statistic is used to measure the similarity of two sets of the data. We evaluate the classification procedure by comparing the throughput of a simulation model when run with mixture models fitted to individual machine breakdown durations; mixture models fitted to group breakdown durations; and raw data. Details of the methods and results of the classification will be presented, and demonstrated using an example. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n4/abs/jors201033a.html [article] Classification analysis for simulation of the duration of machine breakdowns [texte imprimé] / Lu, L., Auteur ; Currie, C. S. M., Auteur ; Cheng, R. C. H., Auteur . - 2011 . - pp. 760–767. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 4 (Avril 2011) . - pp. 760–767 Mots-clés : Simulation  Classification  Manufacturing  Bootstrapping Index. décimale : 001.424 Résumé : Machine failure can have a significant impact on the throughput of manufacturing systems, therefore accurate modelling of breakdowns in manufacturing simulation models is essential. Finite mixture distributions have been successfully used by Ford Motor Company to model machine breakdown durations in simulation models of engine assembly lines. These models can be very complex, with a large number of machines. To simplify the modelling we propose a method of grouping machines with similar distributions of breakdown durations, which we call the Arrows Classification Method, where the Two-Sample Cramér-von-Mises statistic is used to measure the similarity of two sets of the data. We evaluate the classification procedure by comparing the throughput of a simulation model when run with mixture models fitted to individual machine breakdown durations; mixture models fitted to group breakdown durations; and raw data. Details of the methods and results of the classification will be presented, and demonstrated using an example. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n4/abs/jors201033a.html