Functional risk modeling and selective maintenance optimization approach for multi-stage manufacturing system considering operational robustness

• A functional risk based selective maintenance model considering operational robustness is presented. • A selective maintenance optimization method using ASA-PSO is proposed. • A multi-stage manufacturing system example of ferrite phase-shifting unit is provided. Operational robustness of multi-stage manufacturing system is the premise to ensure product quality, and product quality is the direct reflection of the functional risk. Nevertheless, current maintenance strategies often overlook the functional risks and operational robustness of running manufacturing systems. Therefore, a functional risk model and selective maintenance optimization approach considering operational robustness are proposed. First, on the basis of the definition of the operational robustness of multi-stage manufacturing systems, the functional risk formation mechanism is defined, and the principle of selective maintenance is proposed. Second, the synergistic effect between functional risk and operational robustness is expounded, and a comprehensive evaluation model of functional risk considering operational robustness is described. Third, a selective maintenance method that considers robust parameters is proposed to ensure the operational robustness of a multi-stage manufacturing system, and an adaptive simulated annealing-particle swarm optimization (ASA-PSO) algorithm is used to obtain the optimal maintenance decision to maximize operational robustness. Finally, the effectiveness of the proposed method is demonstrated using a ferrite phase-shifting unit manufacturing system as an example.

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Publication Details

Journal
Reliability Engineering & System Safety
Published
2024-12-19
DOI
https://doi.org/10.1016/j.ress.2024.110775
Citations
9
Primary Topic
Reliability and Maintenance Optimization
Type
article
Field-Weighted Citation Impact
3.28
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Functional risk modeling and selective maintenance optimization approach for multi-stage manufacturing system considering operational robustness

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article

Functional risk modeling and selective maintenance optimization approach for multi-stage manufacturing system considering operational robustness

Tianyu Feng, Yihai He, Shuang Yu, Wei Dai, Jiayang Li, Rui Shi
article en
9 citations

Abstract

• A functional risk based selective maintenance model considering operational robustness is presented. • A selective maintenance optimization method using ASA-PSO is proposed. • A multi-stage manufacturing system example of ferrite phase-shifting unit is provided. Operational robustness of multi-stage manufacturing system is the premise to ensure product quality, and product quality is the direct reflection of the functional risk. Nevertheless, current maintenance strategies often overlook the functional risks and operational robustness of running manufacturing systems. Therefore, a functional risk model and selective maintenance optimization approach considering operational robustness are proposed. First, on the basis of the definition of the operational robustness of multi-stage manufacturing systems, the functional risk formation mechanism is defined, and the principle of selective maintenance is proposed. Second, the synergistic effect between functional risk and operational robustness is expounded, and a comprehensive evaluation model of functional risk considering operational robustness is described. Third, a selective maintenance method that considers robust parameters is proposed to ensure the operational robustness of a multi-stage manufacturing system, and an adaptive simulated annealing-particle swarm optimization (ASA-PSO) algorithm is used to obtain the optimal maintenance decision to maximize operational robustness. Finally, the effectiveness of the proposed method is demonstrated using a ferrite phase-shifting unit manufacturing system as an example.

Reliability Engineering & System SafetyVol. 256
Openalex Percentile: Top 8%
Reliability and Maintenance Optimization
3.28
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