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Manufacturing systems: wear modeling and numerical procedures

 

作者: E.K. Boukas,   J. Yang,   G. Yin,   Q. Zhang,  

 

期刊: Stochastic Analysis and Applications  (Taylor Available online 1997)
卷期: Volume 15, issue 3  

页码: 269-293

 

ISSN:0736-2994

 

年代: 1997

 

DOI:10.1080/07362999708809476

 

出版商: Marcel Dekker, Inc.

 

关键词: Manufacturing System;Controlled Markov Process;production Planning;Repair Rate Control;Maintenance Sheduling;Dynamic programming Equation;Stationary Distribution

 

数据来源: Taylor

 

摘要:

Consider a model of a flexible rnanufacturing system with failure-prone machines. The control variables are the rates of maintenance, repair, and production. The objective is to choose these control variables over time that minimize the total cost of over/under stock, repair, and maintenance with either discounted cost or average cost per unit time. The focus of this work is on the modeling and numerical methods for a wear process formulation. A Markov chain approach is used to deal with the approximation problem. The dynamic programming equation is used only for suggesting a good numerical approximation scheme. The convergence result is obtained by deriving the weak convergence of the associated Markov chain. A one machine one part type model is given as an illustration for the numerical experiment

 

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