Timely condition-based maintenance planning for multi-component systems

K. Verbert, B. De Schutter, and R. Babuska, "Timely condition-based maintenance planning for multi-component systems," Reliability Engineering & System Safety, vol. 159, pp. 310-321, Mar. 2017.

Last-minute maintenance planning is often undesirable, as it may cause downtime during operational hours, may require rescheduling of other activities, and does not allow to optimize the management of spare parts, material, and personnel. In spite of the aforementioned drawbacks of last-minute planning, most existing methods plan maintenance activities at the last minute. In this paper, we propose a new strategy for timely maintenance planning in multi-component systems. As a first step, we determine for each system component independently the most appropriate maintenance planning strategy. This way, the maintenance decisions can be tailored to the specific situations. For example, conservative maintenance decisions can be taken when the risk tolerance is low, and maintenance decisions can be made timely when we can accurately predict future degradation behavior. In the second step, we optimize the maintenance plan at the system level. Here, we account for economic and structural dependence with the aim to profit from spreading or combining various maintenance activities. The applicability of the method is demonstrated on a railway case. It is shown how the different cost functions (e.g. costs of maintenance, downtime, and failure) influence the maintenance decisions.

 * Online version of the paper
 * Corresponding technical report: pdf file (574 KB)
      Note: More information on the pdf file format mentioned above can be found here.

Bibtex entry:

        author={K. Verbert and B. {D}e Schutter and R. Babu{\v{s}}ka},
        title={Timely condition-based maintenance planning for multi-component systems},
        journal={Reliability Engineering \& System Safety},

Go to the publications overview page.

This page is maintained by Bart De Schutter. Last update: June 26, 2018.