Optimization for condition-based maintenance with semi-Markov decision process [An article from: Reliability Engineering and System Safety] Buy on Amazon

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Optimization for condition-based maintenance with semi-Markov decision process [An article from: Reliability Engineering and System Safety]

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PublisherElsevier
ISBN / ASINB000RR5VDW
ISBN-13978B000RR5VD7
AvailabilityAvailable for download now
Sales Rank12,434,707
MarketplaceUnited States  🇺🇸

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This digital document is a journal article from Reliability Engineering and System Safety, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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The semi-Markov decision model is a powerful tool in analyzing sequential decision processes with random decision epochs. In this paper, we have built the semi-Markov decision process (SMDP) for the maintenance policy optimization of condition-based preventive maintenance problems, and have presented the approach for joint optimization of inspection rate and maintenance policy. Through numerical examples, the improvement of this method is compared with the scheme, which optimizes only over the inspection rate. We also find that under a special case when the deterioration rate at each failure stage is the same, the optimal policy obtained by SMDP algorithm is a dynamic threshold-type scheme with threshold value depending on the inspection rate.
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