Semi-Markov processes : applications in system reliability and maintenance

✍ Scribed by Franciszek Grabski

Publisher: Elsevier
Year: 2015
Tongue: English
Leaves: 252
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Content:
Front Matter, Pages i-ii
Copyright, Page iv
Dedication, Page v
Preface, Pages xi-xiii
1 - Discrete state space Markov processes, Pages 1-17
2 - Semi-Markov process, Pages 19-35
3 - Characteristics and parameters of SMP, Pages 37-65
4 - Perturbed Semi-Markov processes, Pages 67-82
5 - Stochastic processes associated with the SM process, Pages 83-97
6 - SM models of renewable cold standby system, Pages 99-118
7 - SM models of multistage operation, Pages 119-133
8 - SM model of working intensity process, Pages 135-147
9 - Multitask operation process, Pages 149-160
10 - Semi-Markov Failure Rate Process, Pages 161-176
11 - Simple model of maintenance, Pages 177-186
12 - Semi-Markov model of system component damage, Pages 187-197
13 - Multistate systems with SM components, Pages 199-215
14 - Semi-Markov maintenance nets, Pages 217-228
15 - Semi-Markov decision processes, Pages 229-244
Summary, Page 245
Bibliography, Pages 247-251
Notation, Pages 253-255

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