Litcius/Paper detail

Condition-based maintenance for multi-component systems: Modeling, structural properties, and algorithms

Zhicheng Zhu, Yisha Xiang

2020Figshare34 citationsDOIOpen Access PDF

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 <i>IISE Transaction</i>, datasets, additional tables, detailed proofs, etc.

Topics & Concepts

Component (thermodynamics)Computer scienceAlgorithmMathematical optimizationTime horizonJoinsQuality (philosophy)Condition-based maintenanceMathematicsEngineeringReliability engineeringThermodynamicsPhilosophyEpistemologyPhysicsProgramming languageReliability and Maintenance OptimizationLife Cycle Costing AnalysisSoftware Reliability and Analysis Research