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Semi-Markov Processes: Applications in System Reliability and Maintenance

Autor Franciszek Grabski
en Limba Engleză Hardback – 28 sep 2014
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
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Specificații

ISBN-13: 9780128005187
ISBN-10: 0128005181
Pagini: 270
Ilustrații: colour illustrations
Dimensiuni: 152 x 229 x 16 mm
Greutate: 0.53 kg
Editura: ELSEVIER SCIENCE

Public țintă

mathematicians, engineering practitioners, PhD and MSc students

Cuprins

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

Recenzii

"...a modern and successful monograph of this area...provides a very good look at the current knowledge in this area, offered by a recognized researcher of such kind of stochastic processes." --MathSciNet