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A comparative study of simulation models for the production control of unreliable manufacturing systems

Rivera-Gomez, H. et Gharbi, A. et Kenne, J. P.. 2012. « A comparative study of simulation models for the production control of unreliable manufacturing systems ». In Proceedings of the 4th International Conference on Information Systems, Logistics and Supply Chain : Creative Logistics for an Uncertain World - ILS 2012 (Québec, QC, Canada, Aug. 26-29, 2012)

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Résumé

This paper deals with the production control policy of an unreliable manufacturing system producing one part type, and subject to random failures and repairs. The applied production control policy is based on the so-called hedging point policy (HPP), which consists in building and maintaining a safety stock of product in order to fulfill the demand, and protect the production system against shortages during maintenance actions. The main objective of the study is to determine the most efficient option of the ARENA simulation software that simulates properly the production systems under consideration. To this end, four simulation models mimicking the dynamics and the stochastic behavior of the proposed manufacturing system were developed. Concepts of discrete and continuous simulation and modules from the ARENA flow process template, are applied to develop the models. The hedging point policy is used as input parameter of the simulation models, where we seek to determine the optimal production threshold that minimizes the inventory and backlog cost. Based on simulation results, the performance of the models is evaluated, in terms of accuracy and time economy. The obtained results shows that the continuous simulation model that uses C++ inserts outperforms the other models

Type de document: Compte rendu de conférence
Professeur:
Professeur
Gharbi, Ali
Kenné, Jean-Pierre
Affiliation: Génie de la production automatisée, Génie mécanique
Date de dépôt: 16 févr. 2016 17:11
Dernière modification: 11 mars 2016 15:59
URI: http://espace2.etsmtl.ca/id/eprint/12325

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