A novel approach for modelling complex maintenance systems using discrete event simulation
Autor: | Ashutosh Tiwari, Abdullah Alrabghi |
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Rok vydání: | 2016 |
Předmět: |
0209 industrial biotechnology
Engineering 021103 operations research Operations research business.industry Event (computing) 0211 other engineering and technologies 02 engineering and technology Industrial engineering Industrial and Manufacturing Engineering 020901 industrial engineering & automation Spare part Industrial systems Production (economics) Discrete event simulation Safety Risk Reliability and Quality business Visual interactive simulation Queue Spare parts management |
Zdroj: | Reliability Engineering & System Safety. 154:160-170 |
ISSN: | 0951-8320 |
DOI: | 10.1016/j.ress.2016.06.003 |
Popis: | 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. |
Databáze: | OpenAIRE |
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