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Reliability and Optimal Maintenance

Reliability and Optimal Maintenance

Reliability and Optimal Maintenance aims to present a state-of-the-art survey of theories and methods of reliability, maintenance, and warranty with emphasis on multi-unit systems, and to reflect current hot topics: imperfect maintenance, economic dependence, opportunistic maintenance, quasi-renewal processes, warranty with maintenance and economic dependency, and software testing and maintenance. This book is distinct from others because it consists mainly of research work published on technical journals and conferences in recent years by us and our co-authors.

You can also Read Case Studies in Reliability & Maintenance


  • Introduction
  • Imperfect Maintenance and Dependence
  • Maintenance Policies and Analysis
  • A Quasi-renewal Process and Its Applications
  • Reliability and Optimal Maintenance of Series Systems with Imperfect Repair and Dependence
  • Opportunistic Maintenance of Multi-unit Systems
  • Optimal Preparedness Maintenance of Multi-unit Systems with Imperfect Maintenance and Economic Dependence
  • Optimal Opportunistic Maintenance Policies of k-out-of-n Systems
  • Reliability and Optimal Inspection-maintenance Models of Multi-degraded Systems
  • Warranty Cost Models with Dependence and Imperfect Repair
  • Software Reliability, Cost, and Optimization Models
  • Monte Carlo Reliability Simulation of Complex Systems
  • Appendix Elements of Reliability and Probability
  • References
  • Index

Maintenance involves preventive and unplanned actions carried out to retain a system at or restore it to an acceptable operating condition. Optimal maintenance policies aim to provide optimum system reliability and safety performance at the lowest possible maintenance costs. Proper maintenance techniques have been emphasized in recent years due to increased safety and reliability requirements of systems, increased complexity, and rising costs of material and labor. For some systems, such as aircraft, submarines, and nuclear power stations, it is extremely important to avoid failure during actual operation because it is dangerous and disastrous.

To obtain the optimal maintenance policy for a complex system, it is necessary to determine system availability or MTBF. However, there are some difficulties in evaluating complex large-scale system reliability and availability given confidence levels using classical statistics.


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