Preventive replacement policies with time of operations, mission durations, minimal repairs and maintenance triggering approaches

• Published in: Journal of manufacturing systems Vol. 61; pp. 819 - 829
• Main Authors: Zhao, Xufeng, Cai, Jiajia, Mizutani, Satoshi, Nakagawa, Toshio
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.10.2021; The Society of Manufacturing Engineers. Published by Elsevier Ltd
• Subjects: Failure rate; Minimal repair; Mission duration; Production system; Replacement; Technical Paper; Production system; Replacement; Mission duration; Failure rate; Minimal repair
• ISSN: 0278-6125; 1878-6642; 1878-6642
• DOI: 10.1016/j.jmsy.2020.04.003

•Random arrival times of mission durations are considered for replacement policies.•Random arrival times of mission durations are considered for minimal repairs.•Replacement first policies with mission durations are modeled.•Replacement last policies with mission durations are modeled.•Case illustrations are given via comparing of maintenance first and last policies. When a mission arrives at a random time and lasts for a duration, it becomes an interesting problem to plan replacement policies according to the health condition and repair history of the operating unit, as the reliability is required at mission time and no replacement can be done preventively during the mission duration. From this viewpoint, this paper proposes that effective replacement policies should be collaborative ones gathering data from time of operations, mission durations, minimal repairs and maintenance triggering approaches. We firstly discuss replacement policies with time of operations and random arrival times of mission durations, model the policies and find optimum replacement times and mission durations to minimize the expected replacement cost rates analytically. Secondly, replacement policies with minimal repairs and mission durations are discussed in a similar analytical way. Furthermore, the maintenance triggering approaches, i.e., replacement first and last, are also considered into respective replacement policies. Numerical examples are illustrated when the arrival time of the mission has a gamma distribution and the failure time of the unit has a Weibull distribution. In addition, simple case illustrations of maintaining the production system in glass factories are given based on the assumed data.