期刊
IISE TRANSACTIONS
卷 53, 期 1, 页码 88-100出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/24725854.2020.1741740
关键词
Condition-based maintenance; multi-component systems; multi-stage stochastic integer programming; endogenous uncertainty
资金
- U.S. National Science Foundation [1855408]
- Div Of Civil, Mechanical, & Manufact Inn
- Directorate For Engineering [1855408] Funding Source: National Science Foundation
This article investigates the optimization problem of Condition-Based Maintenance for multi-component systems. It develops a multi-stage stochastic integer model and designs two efficient algorithms to solve the problem. Algorithm 1 provides optimal solutions, while Algorithm 2 heuristically finds high-quality solutions based on Algorithm 1.
Condition-Based Maintenance (CBM) is an effective maintenance strategy to improve system performance while lowering operating and maintenance costs. Real-world systems typically consist of a large number of components with various interactions among components. However, existing studies on CBM mainly focus on single-component systems. Multi-component CBM, which joins the components' stochastic degradation processes and the combinatorial maintenance grouping problem, remains an open issue in the literature. In this article, we study the CBM optimization problem for multi-component systems. We first develop a multi-stage stochastic integer model with the objective of minimizing the total maintenance cost over a finite planning horizon. We then investigate the structural properties of a two-stage model. Based on the structural properties, two efficient algorithms are designed to solve the two-stage model. Algorithm 1 solves the problem to its optimality and Algorithm 2 heuristically searches for high-quality solutions based on Algorithm 1. Our computational studies show that Algorithm 1 obtains optimal solutions in a reasonable amount of time and Algorithm 2 can find high-quality solutions quickly. The multi-stage problem is solved using a rolling horizon approach based on the algorithms for the two-stage problem. are available for this article. Go to the publisher's online edition of IISE Transaction, datasets, additional tables, detailed proofs, etc.
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