On defect propagation in multi-machine stochastically deteriorating systems with incomplete information

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In many manufacturing environments, costly job inspection provides information about the random deterioration of the machines. The resulting maintenance and inspection problem is extensively studied for a single machine system by using the framework of Partially Observable Markov Decision Processes (POMDPs). In this work, this concept is extended to multiple operations and multiple job types by considering two process flow topologies: (i) re-entrant flow, (ii) hybrid flow. The resulting (significantly large sized) POMDPs are solved using a point based method called PERSEUS, and the results are compared with those obtained by conventionally used periodic policies. (C) 2012 Elsevier Ltd. All rights reserved.
Publisher
ELSEVIER SCI LTD
Issue Date
2012-09
Language
English
Article Type
Article
Keywords

OBSERVABLE MARKOV-PROCESSES; DECISION-PROCESSES; HORIZON; MODELS

Citation

JOURNAL OF PROCESS CONTROL, v.22, no.8, pp.1478 - 1489

ISSN
0959-1524
DOI
10.1016/j.jprocont.2012.01.018
URI
http://hdl.handle.net/10203/103362
Appears in Collection
CBE-Journal Papers(저널논문)
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