Stochastic System Reliability Modelling
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Stochastic System Reliability Modeling
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Author : Shunji Osaki
language : en
Publisher: World Scientific
Release Date : 1985
Stochastic System Reliability Modeling written by Shunji Osaki and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Technology & Engineering categories.
Probability theory. Stochastic processes. Markov renewal processes. Stochastic models for one-unit systems. Stochastic models for two-unit redundant systems. Stochastic models for fault-tolerant computing systems. Laplace-stieltjes transforms. Signal-flow graphs.
Stochastic System Reliability Modelling
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Author : Shunji Osaki
language : en
Publisher: World Scientific
Release Date : 1985-10-01
Stochastic System Reliability Modelling written by Shunji Osaki and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985-10-01 with Mathematics categories.
This book aims to present an overview of stochastic system reliability modeling for undergraduate and graduate students, engineers and researchers. It is ideal as a one-semester undergraduate or graduate level text in reliability, applied stochastic processes, stochastic operations research and systems engineering. The topics are divided into two parts: The first part deals with probability theory and stochastic processes, which provide the basic ideas of applied stochastic processes and the second part treats their applications to system reliability modelling. Throughout the later half, Markov renewal processes are applied to formulating stochastic models for system reliability. Since a fairly intermediate level of mathematics is assumed two appendices on Laplace-Stieltjes transforms and signal flow graphs provide much background material. The text is pedagogically sound.
Stochastic System Reliability Modeling
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Author :
language : en
Publisher:
Release Date : 1985
Stochastic System Reliability Modeling written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Reliability (Engineering) categories.
Stochastic Models In Reliability And Maintenance
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Author : Shunji Osaki
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-04
Stochastic Models In Reliability And Maintenance written by Shunji Osaki and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-04 with Business & Economics categories.
This book contains 12 contributions on stochastic models in reliability and maintenance. Written by the leading researchers on each topic, each contribution surveys the current status on stochastic models emphasizing mathematical formulation and optimization applications. Each contribution is self-contained and has a thorough bibliography. The topics include renewal processes, semi-Markov processes, Markovian deterioration models, maintenance and replacement models, software reliability models and Monte-Carlo simulation. This book provides researchers, reliability engineers and graduate students with the current status of the field and future developments of the subject.
Stochastic Models In Reliability Engineering
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Author : Lirong Cui
language : en
Publisher: CRC Press
Release Date : 2020-07-29
Stochastic Models In Reliability Engineering written by Lirong Cui and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-29 with Mathematics categories.
This book is a collective work by many leading scientists, analysts, mathematicians, and engineers who have been working at the front end of reliability science and engineering. The book covers conventional and contemporary topics in reliability science, all of which have seen extended research activities in recent years. The methods presented in this book are real-world examples that demonstrate improvements in essential reliability and availability for industrial equipment such as medical magnetic resonance imaging, power systems, traction drives for a search and rescue helicopter, and air conditioning systems. The book presents real case studies of redundant multi-state air conditioning systems for chemical laboratories and covers assessments of reliability and fault tolerance and availability calculations. Conventional and contemporary topics in reliability engineering are discussed, including degradation, networks, dynamic reliability, resilience, and multi-state systems, all of which are relatively new topics to the field. The book is aimed at engineers and scientists, as well as postgraduate students involved in reliability design, analysis, experiments, and applied probability and statistics.
Predictive Analytics In System Reliability
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Author : Vijay Kumar
language : en
Publisher: Springer Nature
Release Date : 2022-09-08
Predictive Analytics In System Reliability written by Vijay Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-08 with Mathematics categories.
This book provides engineers and researchers knowledge to help them in system reliability analysis using machine learning, artificial intelligence, big data, genetic algorithm, information theory, multi-criteria decision making, and other techniques. It will also be useful to students learning reliability engineering. The book brings readers up to date with how system reliability relates to the latest techniques of AI, big data, genetic algorithm, information theory, and multi-criteria decision making and points toward future developments in the subject.
Markov Processes For Stochastic Modeling
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Author : Oliver Ibe
language : en
Publisher: Newnes
Release Date : 2013-05-22
Markov Processes For Stochastic Modeling written by Oliver Ibe and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-22 with Mathematics categories.
Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. - Presents both the theory and applications of the different aspects of Markov processes - Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented - Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.
Applied Stochastic System Modeling
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Author : Shunji Osaki
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Applied Stochastic System Modeling written by Shunji Osaki and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
This book was written for an introductory one-semester or two-quarter course in stochastic processes and their applications. The reader is assumed to have a basic knowledge of analysis and linear algebra at an undergraduate level. Stochastic models are applied in many fields such as engineering systems, physics, biology, operations research, business, economics, psychology, and linguistics. Stochastic modeling is one of the promising kinds of modeling in applied probability theory. This book is intended to introduce basic stochastic processes: Poisson pro cesses, renewal processes, discrete-time Markov chains, continuous-time Markov chains, and Markov-renewal processes. These basic processes are introduced from the viewpoint of elementary mathematics without going into rigorous treatments. This book also introduces applied stochastic system modeling such as reliability and queueing modeling. Chapters 1 and 2 deal with probability theory, which is basic and prerequisite to the following chapters. Many important concepts of probabilities, random variables, and probability distributions are introduced. Chapter 3 develops the Poisson process, which is one of the basic and im portant stochastic processes. Chapter 4 presents the renewal process. Renewal theoretic arguments are then used to analyze applied stochastic models. Chapter 5 develops discrete-time Markov chains. Following Chapter 5, Chapter 6 deals with continuous-time Markov chains. Continuous-time Markov chains have im portant applications to queueing models as seen in Chapter 9. A one-semester course or two-quarter course consists of a brief review of Chapters 1 and 2, fol lowed in order by Chapters 3 through 6.
Stochastic Reliability Modelling For Complex Systems
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Author : Awelani Malada
language : en
Publisher:
Release Date : 2013
Stochastic Reliability Modelling For Complex Systems written by Awelani Malada and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Two well-known methods of improving the reliability of a system are (i) provision of redundants units, and (ii) repair maintenance. In a redundant system more units are made available for performing the system function when fewer are required exactly. There are two major types of redundancy- parallel and standby. In this thesis we confine to both these redundant systems. A series system is also studied. Some of the typical assumptions made in the analysis of redundant systems are (i) the repair times are assumed to be exponential (ii) the system measures are modeled but not estimated (iii) the system is available continuously (iv) environmental factors not affecting the system (v) the failures take place only in one stage (vi) the switching device is perfect (vii) system reliability for given chance constraints (viii) the time required to transfer a unit from the standby state to the operating stage is negligible (instantaneous switchover) (ix) the failures and repairs are independent. However, we frequently come across systems where one or more of these assumptions have to be dropped. This is the motivation for the detailed study of the models presented in this thesis. In this thesis we present several models of redundant systems relaxing one or more of these assumptions simultaneously. More specifically it is a study of stochastic models of redundant repairable systems with rest period for the operator, non-instantaneous switchover, imperfect switch, intermittent use, and series system optimization. The thesis contains seven chapters. Chapter 1 is introductory in nature and contains a brief description of the mathematical techniques used in the analysis of redundant systems. In chapter 2, a two unit system with Erlangian repair time is studied by relaxing the assumptions (i) and (ii). The difference- differential equations are formulated for the state probabilities, and the system measures like reliability and the availability are obtained over a long run. The asymptotic interval estimation is studied for these system measures. The model has been illustrated numerically. In chapter 3, an n unit system operating intermittently, and in a random environment is studied, by relaxing the assumptions (iii) and (iv). In an intermittently used system, the mean number of disappointments is one of the important measures, which has been obtained for this system in the steady state. In chapter 4, the assumption (v) and (vi) are relaxed. In most of the models studied earlier in reliability analysis is the study of system measures like reliability and availability. In this chapter, profit analysis of a single unit system with three possible modes of the failure of the unit is studied .This chapter consists of two models: in model 1, the unit goes under repair (if a repairman is available) the moment it fails partially, whereas in model 2 the unit goes under repair at complete failure. The repairman appears in, and disappears from, the system randomly. A comparison between these two models has been studied, after calculating numerically the profit and the MTSF. Contrary to the previous chapters, stochastic optimization is studied using the Branch and Bound technique in chapter 5 (relaxing the assumption (vii)). In this chapter, an n unit system operating in a random environment is considered. The environment determines the number of units required for the satisfactory performance of the system. Assuming that a unit in standby can fail and that the environment is described by a Markov process, we obtained expressions for the distribution and the moments of the time to the first disappointment, and the expected number of disappointments over an arbitrary interval (0, t]. In chapter 6, the assumption (viii) is relaxed. The reliability, availability and the busy period analysis is studied with the assumption of the non-instantaneous switchover (the time taken from standby state to the operating state is non-negligible random variable). It is also assumed that the unit has three possible failure modes (normal, partial and total failure). Numerical example illustrated the results obtained. The assumption (ix) is relaxed in chapter 7, and a two-unit cold standby system with the provision of rest for the operating unit is studied. Also, the failure and repair times of each unit assumed to be correlated by taking their joint density as bivariate exponential. The system is observed at suitable regenerative epochs to obtain various reliability characteristics of interest, such as the distribution of time to system failure and its mean, and the steady-state probabilities of the system being in up or down states or under repair. Earlier results are verified as particular cases. Numerical example illustrated the results obtained.
Stochastic Models In Reliability
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Author : Terje Aven
language : en
Publisher: Springer Science & Business Media
Release Date : 1999-03-04
Stochastic Models In Reliability written by Terje Aven and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-03-04 with Mathematics categories.
A comprehensive up-to-date presentation of some of the classical areas of reliability, based on a more advanced probabilistic framework using the modern theory of stochastic processes. This framework allows analysts to formulate general failure models, establish formulae for computing various performance measures, as well as determine how to identify optimal replacement policies in complex situations.