A Dynamic Maintenance Strategy for Multi-Component Systems Using a Genetic Algorithm

Abstract

In multi-component systems, the components are dependent, rather than degenerating independently, leading to changes in maintenance schedules. In this situation, this study proposes a grouping dynamic maintenance strategy. Considering the structure of multi-component systems, the maintenance strategy is determined according to the importance of the components. The strategy can minimize the expected depreciation cost of the system and divide the system into optimal groups that meet economic requirements. First, multi-component models are grouped. Then, a failure probability model of multi-component systems is established. The maintenance parameters in each maintenance cycle are updated according to the failure probability of the components. Second, the component importance indicator is introduced into the grouping model, and the optimization model, which aimed at a maximum economic profit, is established. A genetic algorithm is used to solve the non-deterministic polynomial (NP)-complete problem in the optimization model, and the optimal grouping is obtained through the initial grouping determined by random allocation. An 11-component series and parallel system is used to illustrate the effectiveness of the proposed strategy, and the influence of the system structure and the parameters on the maintenance strategy is discussed.

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“…In [32] the authors presented the use of an ANN and machine learning for predicting ship maintenance and repair labor. In [33], the authors presented this type of strategy. They considered the structure of multicomponent systems; the maintenance strategy was determined according to the importance of the components.…”

“…In their research, the authors proved that the strategy could minimize the expected depreciation cost of the system and the system could be divided into optimal groups that met the economic requirements. Also, different researchers [33] have used predicting methods based on clustering and autoencoders for fault detection and diagnosis of industrial processes. To ensure a reliable maintenance strategy, establishing a plan for the entire maintenance process for the assets, from preliminary asset confirmation through to entering the master data in the management system, is necessary [34].…”