Journal
JOURNAL OF MANUFACTURING SYSTEMS
Volume 55, Issue -, Pages 221-232Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jmsy.2020.03.003
Keywords
Maintenance; Manufacturing systems; Performance evaluation; Markov Chain
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Maintenance decision-making in large manufacturing systems is complex as it requires the integration of various information. A control-limit policy is popular in practice, where maintenance is carried out when the degradation state of a machine reaches a threshold value. In this paper, by developing a framework based on discrete-time Markov chain models, we evaluate the system performance under the control-limit policy, in manufacturing systems that consist of multi-state machines and intermediate buffers. An exact analysis is performed for a two-machine-one-buffer system and an approximation method based on system decomposition is developed for multi-stage systems. Both steady-state and transient performance is analyzed. Numerical examples are presented to demonstrate the accuracy of the proposed method and the impact of different parameters (e.g., buffer capacity, uncertainty in the maintenance duration) on the system performance.
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