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Semi-Markov Processes: Applications in System Reliability and Maintenance is a modern view of discrete state space and continuous time semi-Markov processes and their applications in reliability and maintenance. The book explains how to construct semi-Markov models and discusses the different reliability parameters and characteristics that can be obtained from those models.The book is a useful resource for mathematicians, engineering practitioners, and PhD and MSc students who want to understand the basic concepts and results of semi-Markov process theory.
- Clearly defines the properties and theorems from discrete state Semi-Markov Process (SMP) theory- Describes the method behind constructing Semi-Markov (SM) models and SM decision models in the field of reliability and maintenance- Provides numerous individual versions of SM models, including the most recent and their impact on system reliability and maintenance
Franciszek Grabski is a Full Professor and the Head of the Mathematics and Physics Department at the Naval University in Gdynia, Poland. The main focus of his math research interests focus on probability theory, in particular its applications in system reliability theory and practice. He has constructed and tested several new reliability stochastic models and developed the Bayesian methods applications in reliability.He is the author or co-author of more than 100 scientific papers, course-books and monographs in the probability and reliability field. His main monographs are published in Polish.
1. Random process2. Discrete state space markov processes3. Semi-markov process4. Characteristics of semi-markov process5. Perturbed semi-markov processes6. Stochastic processes associated with semi-markov process7. Models of renewable cold standby system with repair8. Semi-markov models of multi-stage operation9. Semi-markov model of working rate process10. Multi-task operation process11. Semi-markov failure rate process12. Model of renewable series system13. Simple models of maintenance14. Multi-state process of system damage15. Multi-state system with semi-markov components16. Semi-markov maintenance net17. Semi-markov decision processes18. Appendix
