Abstract

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. Supplementary materials are available for this article. Go to the publisher’s online edition of IISE Transaction, datasets, additional tables, detailed proofs, etc.

摘要

基于条件的维护（CBM）是一种有效的维护策略，可以提高系统性能，同时降低运营和维护成本。真实世界的系统通常由大量组件组成，各个组件之间存在各种交互。但是，有关煤层气的现有研究主要集中在单组分系统上。将组件的随机退化过程和组合维护分组问题联系在一起的多组件CBM，仍然是文献中的一个未解决的问题。在本文中，我们研究了多组件系统的CBM优化问题。我们首先开发一个多阶段随机整数模型，其目的是在有限的计划范围内将总维护成本降至最低。然后，我们研究了两阶段模型的结构特性。根据结构特性，设计了两种有效的算法来求解两阶段模型。算法1解决了其最优性问题，算法2在算法1的基础上试探性地寻找高质量的解决方案。我们的计算研究表明，算法1在合理的时间内获得了最优解，而算法2可以快速找到高质量的解决方案。基于两阶段问题的算法，使用滚动视野方法解决了多阶段问题。补充材料可用于本文。转到发行商的在线版本 我们的计算研究表明，算法1在合理的时间内获得了最优解，而算法2可以快速找到高质量的解。基于两阶段问题的算法，使用滚动视野方法解决了多阶段问题。补充材料可用于本文。转到发行商的在线版本 我们的计算研究表明，算法1在合理的时间内获得了最优解，而算法2可以快速找到高质量的解。基于两阶段问题的算法，使用滚动视野方法解决了多阶段问题。补充材料可用于本文。转到发行商的在线版本IISE事务，数据集，附加表，详细证明等。