Open Access

ARTICLE

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

Dongyan Shi^1,*, Hui Ma¹, Chunlong Ma^1,2

1 Department of Mechanical and Electrical Engineering, Harbin Engineer University, Harbin, 150006, China
2 Department of Automotive, Harbin Vocational & Technical College, Harbin, 150000, China

* Corresponding Author: Dongyan Shi. Email:

(This article belongs to the Special Issue: Computer-Aided Structural Integrity and Safety Assessment)

Computer Modeling in Engineering & Sciences 2023, 134(3), 1899-1923. https://doi.org/10.32604/cmes.2022.022444

Received 10 March 2022; Accepted 09 May 2022; Issue published 20 September 2022

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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