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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