Optimisation of preventive maintenance grouping strategy for multi-component series systems: Particle swarm based approach. (December 2016)

• Record Type: Journal Article
• Authors: Chalabi, N.; Dahane, M.; Beldjilali, B.; Neki, A.
• Is Part Of: Computers & industrial engineering. Volume 102(2016)
• Page Start: 440
• Page End: 451
• Publication Date: 2016-12
• Subjects: Preventive maintenance -- Maintenance grouping -- Economic dependence -- Multi-component system -- Particle Swarm Optimization (PSO); Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2016.04.018
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Preventive maintenance grouping in series system is studied. Particle swarm optimisation is applied to resolve a multi-objective problem. The approach aims to minimize the cost and maximize the system availability. The obtained results are compared with those ones reported inXia, Xi, Zhou, and Lee (2012) . Abstract: Preventive maintenance is widely accepted within the industry as an effective means to reduce the number of failures and keep manufacturing systems in good conditions. This paper presents an optimization of the grouping strategy of preventive maintenance actions for multi-unit series production systems. Such systems bring a positive economic dependence which make necessary to combine maintenance activities to ensure a low maintenance cost and high system availability. The proposed approach aims to optimize two objectives: improve the availability of the system and minimize the cost of the preventive maintenance. In this paper, a Particle Swarm Optimization (PSO) algorithm is implemented to determine the best planning of maintenance grouping. We conducted several experimentations on different component system scenarios. The obtained results are compared with those ones reported in the literature.