Articoli correlati a Semi-Markov Processes: Applications in Sytem Reliability...

Semi-Markov Processes: Applications in Sytem Reliability and Maintenance - Rilegato

Grabski, Franciszek

 
9780128005187: Semi-Markov Processes: Applications in Sytem Reliability and Maintenance

Sinossi

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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Informazioni sull'autore

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.

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Altre edizioni note dello stesso titolo

9780128102619: Semi-markov Processes: Applications in System Reliability and Maintenance

Edizione in evidenza

ISBN 10:  0128102616 ISBN 13:  9780128102619
Casa editrice: Elsevier Science Ltd, 2017
Brossura