Integrated scheduling of preventive maintenance and renewal projects for multi-unit systems with grouping and balancing. (August 2017)

• Record Type: Journal Article
• Authors: Pargar, Farzad; Kauppila, Osmo; Kujala, Jaakko
• Is Part Of: Computers & industrial engineering. Volume 110(2017)
• Page Start: 43
• Page End: 58
• Publication Date: 2017-08
• Subjects: Maintenance -- Renewal -- Scheduling -- Grouping -- Mathematical modeling -- Downtime minimization; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.05.024
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: We study preventive maintenance and renewal scheduling problem. An integrated approach with grouping and balancing is proposed for multi-unit systems. A pure integer programming model is developed to formulate the considered problem. Two heuristic algorithms based on decomposition approach are developed. We examine our heuristics efficiency via generating and solving numerical examples. A case study on railway is studied and resulted in 14% reduction in maintenance cost. Abstract: This paper studies preventive maintenance and renewal scheduling for multi-unit systems. We develop an integrated optimization method to schedule preventive maintenance and renewal projects by grouping them and simultaneously finding the optimal balance between them. Grouping and balancing are resource utilization techniques to reduce the costs of maintenance without reducing the level of maintenance. We next model the problem as a pure integer linear programming formulation to minimize the costs of maintenance and renewal projects and their relevant preparatory works and downtime costs over the planning horizon. We use a numerical experiment with sensitivity analysis to illustrate the model, and the potential cost reductions that using such an integrated model may lead to. Applications of this model arise in the maintenance of railways, roadways, electricity distribution networks, and distributed pipeline assets. Due to the complexity of the model, two heuristic algorithms based on decomposition approach with problem-specific cutting planes are applied to tackle the problem. Experimental results show that our integrated optimization approach performs well in reducing the cost of preparatory works through proper scheduling. Finally, a case study for the maintenance of railway track shows that using our integrated approach reduces the maintenance and renewal costs by up to 14% as compared with the spreadsheet based approach used currently at the operation.