Maintenance Plan Optimization For A Train Fleet
Author(s)
K. Doganay & M. Bohlin
Abstract
Maintenance planning is an important problem for railways, as well as other application
domains that employ machinerywith expensive replacements and high downtime
costs. In a previous paper, we have developed methods for efficiently finding
optimized maintenance schedules for a single unit, and proposed that the maintenance
plan should be continuously re-optimized based on the condition of components.
However, fleet-level resources, such as the availability of expensive spare
parts, have largely been ignored. In this paper, we extend our previous approach by
proposing a solution for the fleet level maintenance scheduling problem with spare
parts optimization. The new solution is based on a mixed integer linear programming
formulation of the problem. We demonstrate the merits of our approach by
optimizing instances of maintenance schedules based on maintenance data from
railway companies operating in Sweden.
Keywords: maintenance planning, condition based maintenance, optimization, mixed
integer programming, railways.
1 Introduction
Maintenance planning is an important issue, especially for application areas where
high cost machinery is used, and when time spent on maintenance disrupts the
operation and causes losses, monetary or otherwise. Industry often fears that introducing
condition based maintenance (CBM) will lead to more frequent service
interventions, which could counter the potential value of implementing CBM.
Implementation should therefore be done with care, as the maintenance planning
process under CBM needs to be adapted to a much more dynamic situation.
We have previously [1] proposed to harvest the full potential value in CBM
for rail vehicle maintenance using a combination of condition monitoring and
onlinemaintenance planning.A side effect of using this dynamic approach, instead
Keywords
maintenance planning, condition based maintenance, optimization, mixed
integer programming, railways
Related Book
Other papers in this volume
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