Maintenance grouping strategy for multi-component systems with dynamic contexts

• A dynamic grouping maintenance strategy for complex structure systems is proposed.
• Impacts of the system structure on grouping maintenance are investigated.
• A grouping approach based on the rolling horizon and GA algorithm is proposed.
• Different dynamic contexts and their impacts on grouping maintenance are studied.
• The proposed approach can help to update the maintenance planning in dynamic contexts.

This paper presents a dynamic maintenance grouping strategy for multi-component systems with both “positive” and “negative” economic dependencies. Positive dependencies are commonly due to setup cost whereas negative dependencies are related to shutdown cost. Actually, grouping maintenance activities can save part of the setup cost, but can also in the same time increase the shutdown cost. Until now, both types of dependencies have been jointly taken into account only for simple system structures as pure series. The first aim of this paper is to investigate the case of systems with any combination of basic structures (series, parallel or k-out-of n structures). A cost model and a heuristic optimization scheme are proposed since the optimization of maintenance grouping strategy for such multi-component systems leads to a NP-complete problem. Then the second objective is to propose a finite horizon (dynamic) model in order to optimize online the maintenance strategy in the presence of dynamic contexts (change of the environment, the working condition, the production process, etc). A numerical example of a 16-component system is finally introduced to illustrate the use and the advantages of the proposed approach in the maintenance optimization framework.