A novel approach for modelling complex maintenance systems using discrete event simulation. (October 2016)

• Record Type: Journal Article
• Authors: Alrabghi, Abdullah; Tiwari, Ashutosh
• Is Part Of: Reliability engineering & system safety. Volume 154(2016:Oct.)
• Page Start: 160
• Page End: 170
• Publication Date: 2016-10
• Subjects: CBM Condition Based Maintenance -- CM corrective maintenance -- DES Discrete Event Simulation -- METBF Mean Elapsed Time Between Failures -- OM opportunistic maintenance -- PM preventive maintenance -- TTF Time To Failure -- SA Simulated Annealing; Simulation -- Maintenance -- Discrete Event Simulation -- Rapid modelling; 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.2016.06.003
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: Existing approaches for modelling maintenance rely on oversimplified assumptions which prevent them from reflecting the complexity found in industrial systems. In this paper, we propose a novel approach that enables the modelling of non-identical multi-unit systems without restrictive assumptions on the number of units or their maintenance characteristics. Modelling complex interactions between maintenance strategies and their effects on assets in the system is achieved by accessing event queues in Discrete Event Simulation (DES). The approach utilises the wide success DES has achieved in manufacturing by allowing integration with models that are closely related to maintenance such as production and spare parts systems. Additional advantages of using DES include rapid modelling and visual interactive simulation. The proposed approach is demonstrated in a simulation based optimisation study of a published case. The current research is one of the first to optimise maintenance strategies simultaneously with their parameters while considering production dynamics and spare parts management. The findings of this research provide insights for non-conflicting objectives in maintenance systems. In addition, the proposed approach can be used to facilitate the simulation and optimisation of industrial maintenance systems. Highlights: This research is one of the first to optimise maintenance strategies simultaneously. New insights for non-conflicting objectives in maintenance systems. The approach can be used to optimise industrial maintenance systems.