The scheduling of maintenance. A resource-constraints mixed integer linear programming model. (September 2015)

• Record Type: Journal Article
• Authors: Manzini, Riccardo; Accorsi, Riccardo; Cennerazzo, Teresa; Ferrari, Emilio; Maranesi, Fausto
• Is Part Of: Computers & industrial engineering. Volume 87(2015)
• Page Start: 561
• Page End: 568
• Publication Date: 2015-09
• Subjects: Scheduling -- Reliability -- Maintenance action scheduling -- Preventive maintenance -- Corrective maintenance -- Mixed integer linear programming (MILP); Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2015.06.006
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: This paper presents and applies an original MILP model for scheduling preventive maintenance of complex machines made of hundreds of components. This model is cost-based, reliability-based and time resource constraints. Effective for real applications with a large number of tasks, service orders and spare parts. Applied to a significant case study in a what-if environment. Abstract: The scheduling of preventive maintenance is crucial in reliability and maintenance engineering. Hundreds of parts compose complex machines that require replacement and/or repairing. Maintenance involves the machine vendor (1), the machine user (2) and the service maintenance provider (3). The vendor and the maintenance service provider have to guarantee a high level of availability and productivity of the machines and maintain their down-time at a minimum even though they are installed worldwide and usually far from the vendor's headquarters and/or the locations of the provider's regional service offices. Moreover, many companies have great profits from maintenance and spare parts management. This study aims to illustrate an original mixed integer linear programming (MILP) model for the cost-based, reliability-based and resource-constraints scheduling of preventive maintenance actions. The model minimizes the total cost function made of spare parts contributions, the cost of the execution of the preventive actions and the cost of the additional repair activity in case of unplanned failure. The cost of the personnel of the producer and/or the maintenance service provider is also included. Finally, the paper presents a case study in a what-if environment demonstrating the effectiveness and the novelty of this study in real and complex applications.