An optimization framework for opportunistic planning of preventive maintenance activities. (November 2021)

• Record Type: Journal Article
• Authors: Mena, R.; Viveros, P.; Zio, E.; Campos, S.
• Is Part Of: Reliability engineering & system safety. Volume 215(2021)
• Publication Date: 2021-11
• Subjects: Preventive maintenance -- Opportunistic maintenance grouping -- Maintenance activities planning -- Mixed-integer linear programming; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2021.107801
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: Methodologies for designing maintenance policies, such as Reliability Centered Maintenance (RCM), provide a list of recommended preventive maintenance (PM) activities as well as the periodicity for their execution, to comply with safety and reliability standards. This information is then used to elaborate PM plans, defining the instants of execution of each PM activity in the policy throughout a planning horizon, while assuring adequate levels of equipment availability, labor and resource coordination, and spare parts management. Preferably, it is sought to group PM activities executions to form opportunistic work packages to reduce functionality interruptions on the equipment. To address the latter issue, this paper presents an optimization framework for the medium-term opportunistic planning of PM activities on a single machine. The proposed framework is formulated as a computationally tractable continuous time mixed-integer linear program (MILP) that determines the execution instants of PM activities, considering time window tolerances for advancing or delaying executions to maximize the number of grouped executions or, equivalently, minimizing the number of stoppages needed to comply with a PM policy. Diverse numerical experiments are conducted, considering variants of the model regarding the conservativeness in use of the time window tolerances and the inclusion of resource constraints for planning. The results show that the reductions on the number of stoppages of the PM plans, that can be achieved from different levels of time window tolerances, are more significant for PM policies composed by activities with more heterogeneous periodicities of execution. Highlights: The mid-term preventive maintenance planning problem for one machine is addressed. Opportunistic packages of activities are needed to reduce the number of stoppages. An efficient continuous time MILP optimization framework is presented. An extension including resources availability constraints is proposed and studied. Numerical experiments show substantial savings in the number of stoppages.