A Novel Framework for Simulation-based Optimisation of Maintenance Systems

Alrabghi, Abdullah; Tiwari, Ashutosh

doi:10.2507/ijsimm15(1)2.316

Cited by 10 publications

(12 citation statements)

References 27 publications

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“…Very little was found in prior studies on discussing the scope of optimisation, investigating applicable maintenance strategies or formulating the optimal problem [5]. However, in the current research, the simulation-based optimisation framework [13] guided the process of connecting the simulation model to the optimisation engine. Application of the framework resulted in proper discussion of optimisation scope, applicable maintenance strategies and optimal problem formulation for each case.…”

Section: Discussionmentioning

confidence: 95%

Simulation-based optimisation of maintenance systems: Industrial case studies

Alrabghi

Tiwari

Savill

2017

Journal of Manufacturing Systems

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Investigating the optimum blend of maintenance strategies for a given manufacturing system is a continuing concern amongst maintenance academics and professionals. Recent evidence suggests that little research is conducted on the simulation optimisation of maintenance in industrial systems. This study was designed to make an important contribution to the field of simulation-based optimisation of maintenance by presenting two empirical case studies: a tyre re-treading factory and a petro-chemical plant. It is one of the first to optimise various maintenance strategies simultaneously with their parameters in industrial manufacturing systems while considering production dynamics. Stochastic Discrete Event Simulation models were developed and connected to a Multi-Objective Optimisation engine. Various maintenance strategies were investigated including Corrective Maintenance, Preventive Maintenance, Opportunistic Maintenance and Condition-Based Maintenance. The results of this research suggest that over-looking the optimisation of maintenance on the strategic level may lead to sub-optimal solutions. In addition, it appears that traditional trade-offs between maintenance cost and production throughput are not present in some maintenance systems. This is an interesting observation that requires further investigation and experimentation.

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Section: Discussionmentioning

confidence: 95%

Simulation-based optimisation of maintenance systems: Industrial case studies

Alrabghi

Tiwari

Savill

2017

Journal of Manufacturing Systems

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“…In this section, we demonstrate the application of the modelling approach through a simulation optimisation study of a published case [24]. In order to optimise the maintenance system, we follow the simulation-based optimisation framework suggested by Alrabghi and Tiwari [14].…”

Section: Manage the Effects Of Maintenance Actions On The Same Assetmentioning

confidence: 99%

“…In addition, these approaches are used to model one maintenance strategy only. As a result, the choice of maintenance strategies cannot be optimised using frameworks such as the one suggested by Alrabghi and Tiwari [14]. Arab et al [15] modelled both maintenance and production systems.…”

Section: Introductionmentioning

confidence: 99%

A novel approach for modelling complex maintenance systems using discrete event simulation

Alrabghi

Tiwari

2016

Reliability Engineering & System Safety

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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.

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“…So far, few studies have been carried out on the product blockage and machine faults occurring during the product processing on assembly lines [19][20]. When there is any machine fault, the original scheduling scheme may no longer be the optimal one and needs to be redesigned, which means, re-scheduling strategy needs to be used to address the uncertainties in flow shop scheduling brought by product blockage and machine faults [21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Objective Scheduling Optimization Model Considering Product Blockage and Machine Faults

Yin¹,

Liu²,

Yeh³

2017

Int. j. simul. model.

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Considering problems like product blockage and machine faults in the batch scheduling of product assembly lines, this paper proposes a multi-objective flow shop batch scheduling model taking these problems into account, and by comparing with the traditional flow shop scheduling model, it verifies the feasibility and superiority of this model. The results show that, regarding the product blockage problem, this paper improves the MWH heuristic algorithm, leading to better quality of the initial population produced; and that it also proposes a new ISBOX crossover operator algorithm, which is used in combination with the nondominated solution information to calculate the new solution for offsprings, improving the local search capability of the algorithm. In order to address machine faults, this paper obtains new solutions by optimizing the maximum completion time and the early completion time, takes the new solutions as the initial population, and uses the proposed model to optimize the robustness and stability of the existing algorithm. By comparing the proposed model and the traditional scheduling model in terms of product blockage and machine fault, this paper finds that the proposed algorithm has high local and global convergence, and generates high-quality nondominated solutions. According to the re-scheduling strategy, this algorithm can effectively reduce the effects of product blockage and machine faults on the objective function.

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A Novel Framework for Simulation-based Optimisation of Maintenance Systems

Cited by 10 publications

References 27 publications

Simulation-based optimisation of maintenance systems: Industrial case studies

Simulation-based optimisation of maintenance systems: Industrial case studies

A novel approach for modelling complex maintenance systems using discrete event simulation

A Multi-Objective Scheduling Optimization Model Considering Product Blockage and Machine Faults

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