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Simultaneous determination of production and maintenance schedules using in‐line equipment condition and yield information
Author(s) -
Sloan Thomas
Publication year - 2008
Publication title -
naval research logistics (nrl)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 68
eISSN - 1520-6750
pISSN - 0894-069X
DOI - 10.1002/nav.20270
Subject(s) - production (economics) , product (mathematics) , computer science , production line , markov decision process , maintenance actions , reliability engineering , yield (engineering) , quality (philosophy) , operations research , outcome (game theory) , condition based maintenance , process (computing) , markov chain , reliability (semiconductor) , markov process , preventive maintenance , work (physics) , mathematics , engineering , statistics , economics , philosophy , materials science , mathematical economics , macroeconomics , operating system , power (physics) , geometry , epistemology , quantum mechanics , machine learning , metallurgy , mechanical engineering , physics
Abstract In many manufacturing environments, equipment condition has a significant impact on product quality, or yield. This paper presents a semi‐Markov decision process model of a single‐stage production system with multiple products and multiple maintenance actions. The model simultaneously determines maintenance and production schedules, accounting for the fact that equipment condition affects the yield of each product differently. It extends earlier work by allowing the expected time between decision epochs to vary by both action and machine state, by allowing multiple maintenance actions, and by treating the outcome of maintenance as less than certain. Sufficient conditions are developed that ensure the monotonicity of both the optimal production and maintenance actions. While the maintenance conditions closely resemble previously studied conditions for this type of problem, the production conditions represent a significant departure from earlier results. The simultaneous solution method is compared to an approach commonly used in industry, where the maintenance and production problems are treated independently. Solving more than one thousand test problems confirms that the combination of both features of the model—accounting for product differences and solving the problems simultaneously—has a significant impact on performance. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2008