This book is a detailed introduction to selective maintenance and updates readers on recent advances in this field, emphasizing mathematical formulation and optimization techniques. The book is useful for reliability engineers and managers engaged in the practice of reliability engineering and maintenance management. It also provides references that will lead to further studies at the end of each chapter. This book is a reference for researchers in reliability and maintenance and can be used as an advanced text for students.
Author(s): Yu Liu, Hong-Zhong Huang, Tao Jiang
Series: Springer Series in Reliability Engineering
Publisher: Springer
Year: 2023
Language: English
Pages: 196
City: Cham
Preface
Contents
1 Introduction
1.1 Overview of Maintenance Optimization
1.1.1 Paradigms of Maintenance Optimization
1.1.2 System Degradation Characteristics
1.1.3 Maintenance Efficiencies
1.1.4 Inspection Strategies
1.1.5 Multi-component Systems
1.1.6 Maintenance Objectives
1.1.7 Optimization Algorithms
1.2 Selective Maintenance
1.2.1 System Modelling
1.2.2 Efficiency of Maintenance Actions
1.2.3 Constraints of Maintenance Resources
1.2.4 Mission Characteristics and Operating Environment
1.2.5 Solution Algorithms
References
2 Basic Selective Maintenance Model
2.1 Introduction
2.2 Problem Statements and Model Assumptions
2.2.1 Problem Statements
2.2.2 Model Assumptions
2.3 Decision Variables
2.4 Probability of a System Successfully Completing a Mission
2.4.1 Survival Probability of a Component
2.4.2 Typical Lifetime Distribution
2.4.3 Probability of a System Successfully Completing the Next Mission
2.5 Selective Maintenance Modelling
2.5.1 Constraints of Selective Maintenance Problems
2.5.2 Optimization Models of Selective Maintenance Problems
2.6 Illustrative Example
2.7 Closure
References
3 Selective Maintenance for Multi-state Systems under Imperfect Maintenance
3.1 Introduction
3.2 Problem Statements and Model Assumptions
3.3 Imperfect Maintenance and Its Cost
3.4 Probability of a System Successfully Completing a Mission
3.5 Selective Maintenance Modelling
3.6 Illustrative Examples
3.6.1 A Three-Component System
3.6.2 A Multi-state Coal Transportation System
3.7 Closure
References
4 Selective Maintenance for Multi-state Systems with Loading Strategy
4.1 Introduction
4.2 Problem Statements and Model Assumptions
4.3 Imperfect Maintenance
4.3.1 Failure Rate with Load Distribution
4.3.2 Imperfect Maintenance Modelling
4.4 Probability of a System Successfully Completing a Mission
4.5 Selective Maintenance Modelling
4.6 Illustrative Example
4.7 Closure
References
5 Selective Maintenance under Stochastic Time Durations of Breaks and Maintenance Actions
5.1 Introduction
5.2 Problem Statements and Model Assumptions
5.3 Probability of a System Successfully Completing a Mission
5.3.1 Probability Distribution of the Number of Completed Maintenance Actions
5.3.2 Saddlepoint Approximation
5.3.3 Probability of a System Successfully Completing the Next Mission
5.4 Selective Maintenance Optimization
5.4.1 Selective Maintenance Optimization Modelling
5.4.2 Tailored Ant Colony Optimization Algorithm
5.5 Illustrative Examples
5.5.1 A Four-Component System
5.5.2 A Multi-state Coal Transportation System
5.6 Closure
References
6 Robust Selective Maintenance under Imperfect Observations
6.1 Introduction
6.2 Problem Statements and Model Assumptions
6.3 Imperfect Maintenance Model
6.4 Survival Probability of a Component under Imperfect Observations
6.4.1 State and Effective Age under Imperfect Observations
6.4.2 State and Effective Age after Maintenance
6.4.3 Survival Probability of a Component
6.5 Probability of a System Successfully Completing a Mission
6.6 Robust Selective Maintenance Modelling
6.7 Illustrative Examples
6.7.1 A Five-Component System
6.7.2 A Coal Transportation System
6.8 Closure
References
7 Selective Maintenance and Inspection Optimization for Partially Observable Systems
7.1 Introduction
7.2 Problem Statements and Model Assumptions
7.2.1 Problem Statement
7.2.2 Imperfect Maintenance Model
7.2.3 Imperfect Inspection Model
7.3 Joint Selective Maintenance and Inspection Optimization
7.3.1 Probability of a System Successfully Completing a Mission
7.3.2 Mixed Observability Markov Decision Process
7.3.3 Dynamic Programming Algorithm
7.3.4 Deep Reinforcement Learning Algorithm
7.4 Illustrative Examples
7.4.1 A Five-Component System
7.4.2 A Multi-state Coal Transportation System
7.5 Closure
References
8 Selective Maintenance for Systems Operating Multiple Consecutive Missions
8.1 Introduction
8.2 Problem Statements and Model Assumptions
8.3 Imperfect Maintenance Model
8.4 Survival Probability of a Component
8.5 Probability of a System Successfully Completing Missions
8.5.1 Probability of a Component Successfully Completing Future Missions
8.5.2 Probability of a System Successfully Completing Future Missions
8.6 Selective Maintenance Optimization
8.6.1 Selective Maintenance Optimization Model
8.6.2 Customized Simulated Annealing-Based Genetic Algorithm
8.7 Illustrative Examples
8.7.1 A Five-Component System
8.7.2 A Coal Transportation System
8.8 Closure
References
9 Dynamic Selective Maintenance for Multi-state Systems Operating Multiple Consecutive Missions
9.1 Introduction
9.2 Problem Statements and Model Assumptions
9.3 Imperfect Maintenance Model
9.4 Dynamic Selective Maintenance Modelling
9.4.1 States and Effective Ages of Components at the End of a Mission
9.4.2 Probability of System Successfully Completing a Mission
9.4.3 Markov Decision Process Formulation
9.5 Customized Deep Reinforcement Learning Method
9.5.1 Actor-Critic Framework
9.5.2 Agent Training: Experience Replay and Target Network
9.6 Illustrative Examples
9.6.1 A Four-Component System
9.6.2 A Multi-state Coal Transportation System
9.7 Closure
References
Appendix Appendix Parameters for the Multi-state Coal Transportation System in Chapter 7
