Stochastic Models in Reliability and Maintenance
Stochastic Models in Reliability and Maintenance

Author: Shunji Osaki

Publisher: Springer Science & Business Media

Published: 2012-11-02

Total Pages: 338

ISBN-13: 3540248080

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Our daily lives can be maintained by the high-technology systems. Computer systems are typical examples of such systems. We can enjoy our modern lives by using many computer systems. Much more importantly, we have to maintain such systems without failure, but cannot predict when such systems will fail and how to fix such systems without delay. A stochastic process is a set of outcomes of a random experiment indexed by time, and is one of the key tools needed to analyze the future behavior quantitatively. Reliability and maintainability technologies are of great interest and importance to the maintenance of such systems. Many mathematical models have been and will be proposed to describe reliability and maintainability systems by using the stochastic processes. The theme of this book is "Stochastic Models in Reliability and Main tainability. " This book consists of 12 chapters on the theme above from the different viewpoints of stochastic modeling. Chapter 1 is devoted to "Renewal Processes," under which classical renewal theory is surveyed and computa tional methods are described. Chapter 2 discusses "Stochastic Orders," and in it some definitions and concepts on stochastic orders are described and ag ing properties can be characterized by stochastic orders. Chapter 3 is devoted to "Classical Maintenance Models," under which the so-called age, block and other replacement models are surveyed. Chapter 4 discusses "Modeling Plant Maintenance," describing how maintenance practice can be carried out for plant maintenance.

Stochastic Models in Reliability Engineering
Stochastic Models in Reliability Engineering

Author: Lirong Cui

Publisher: CRC Press

Published: 2020-09-01

Total Pages: 402

ISBN-13: 1000094618

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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, and 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, and experiments and applied probability and statistics.

Stochastic Reliability Modeling, Optimization And Applications
Stochastic Reliability Modeling, Optimization And Applications

Author: Syouji Nakamura

Publisher: World Scientific

Published: 2009-11-12

Total Pages: 317

ISBN-13: 9814467553

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Reliability theory and applications become major concerns of engineers and managers engaged in making high quality products and designing highly reliable systems. This book aims to survey new research topics in reliability theory and useful applied techniques in reliability engineering.Our research group in Nagoya, Japan has continued to study reliability theory and applications for more than twenty years, and has presented and published many good papers at international conferences and in journals. This book focuses mainly on how to apply the results of reliability theory to practical models. Theoretical results of coherent, inspection, and damage systems are summarized methodically, using the techniques of stochastic processes. There exist optimization problems in computer and management sciences and engineering. It is shown that such problems as computer, information and network systems are solved by using the techniques of reliability. Furthermore, some useful techniques applied to the analysis of stochastic models in management science and plants are shown.The reader will learn new topics and techniques, and how to apply reliability models to actual ones. The book will serve as an essential guide to a subject of study for graduate students and researchers and as a useful guide for reliability engineers engaged not only in maintenance work but also in management and computer works.

Stochastic Processes
Stochastic Processes

Author: Toshio Nakagawa

Publisher: Springer Science & Business Media

Published: 2011-05-27

Total Pages: 254

ISBN-13: 0857292749

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Reliability theory is of fundamental importance for engineers and managers involved in the manufacture of high-quality products and the design of reliable systems. In order to make sense of the theory, however, and to apply it to real systems, an understanding of the basic stochastic processes is indispensable. As well as providing readers with useful reliability studies and applications, Stochastic Processes also gives a basic treatment of such stochastic processes as: the Poisson process, the renewal process, the Markov chain, the Markov process, and the Markov renewal process. Many examples are cited from reliability models to show the reader how to apply stochastic processes. Furthermore, Stochastic Processes gives a simple introduction to other stochastic processes such as the cumulative process, the Wiener process, the Brownian motion and reliability applications. Stochastic Processes is suitable for use as a reliability textbook by advanced undergraduate and graduate students. It is also of interest to researchers, engineers and managers who study or practise reliability and maintenance.

On the Use of Stochastic Processes in Modeling Reliability Problems
On the Use of Stochastic Processes in Modeling Reliability Problems

Author: Alessandro Birolini

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 113

ISBN-13: 3642465536

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Stochastic processes are powerful tools for the investigation of reliability and availability of repairable equipment and systems. Because of the involved models, and in order to be mathematically tractable, these processes are generally confined to the class of regenerative stochastic processes with a finite state space, to which belong: renewal processes, Markov processes, semi-Markov processes, and more general regenerative processes with only one (or a few) regeneration staters). The object of this monograph is to review these processes and to use them in solving some reliability problems encountered in practical applications. Emphasis is given to a comprehensive exposition of the analytical procedures, to the limitations in volved, and to the unification and extension of. the models known in the literature. The models investigated here assume. that systems have only one repair crew and that no further failure can occur at system down. Repair and failure rates are general ized step-by-step, up to the case in which the involved process is regenerative with only one (or a few) regeneration state(s). Investigations deal with different kinds of reliabilities and availabilities for series/parallel structures. Preventive main tenance and imperfect switching are considered in some examples.

Maintenance Theory of Reliability
Maintenance Theory of Reliability

Author: Toshio Nakagawa

Publisher: Springer Science & Business Media

Published: 2006-03-30

Total Pages: 275

ISBN-13: 1846282217

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Many serious accidents have happened in the world where systems have been large-scale and complex, and have caused heavy damage and a social sense of instability. Furthermore, advanced nations have almost ?nished public inf- structureandrushedintoamaintenanceperiod.Maintenancewillbemore- portant than production, manufacture, and construction, that is, more ma- tenance for environmental considerations and for the protection of natural resources. From now on, the importance of maintenance will increase more and more. In the past four decades, valuable contributions to maintenance policies in reliability theory have been made. This book is intended to s- marize the research results studied mainly by the author in the past three decades. The book deals primarily with standard to advanced problems of main- nance policies for system reliability models. System reliability can be mainly improved by repair and preventive maintenance, and replacement, and rel- bility properties can be investigated by using stochastic process techniques. The optimum maintenance policies for systems that minimize or maximize appropriate objective functions under suitable conditions are discussed both analytically and practically. The book is composed of nine chapters. Chapter 1 is devoted to an int- duction to reliability theory, and brie?y reviews stochastic processes needed for reliability and maintenance theory. Chapter 2 summarizes the results of repair maintenance, which is the most basic maintenance in reliability. The repair maintenance of systems such as the one-unit system and multiple-unit redundant systems is treated. Chapters 3 through 5 summarize the results of three typical maintenance policies of age, periodic, and block replacements.

Shock and Damage Models in Reliability Theory
Shock and Damage Models in Reliability Theory

Author: Toshio Nakagawa

Publisher: Springer Science & Business Media

Published: 2007-02-01

Total Pages: 191

ISBN-13: 1846284422

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This is the first monograph which presents shock and damage models in reliability from introduction to application. Stochastic processes are introduced before current developments are surveyed. The practical applications of shock and damage models are demonstrated using case studies. The author is a leading researcher in this field with more than thirty years of experience. Reliability engineers and managers of maintenance work will find this book a broad reference.

Stochastic Ageing and Dependence for Reliability
Stochastic Ageing and Dependence for Reliability

Author: Chin Diew Lai

Publisher: Springer Science & Business Media

Published: 2006-09-24

Total Pages: 437

ISBN-13: 038734232X

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This book provides a panoramic view of theory and applications of Ageing and Dependence in the use of mathematical methods in reliability and survival analysis. Ageing and dependence are important characteristics in reliability and survival analysis. They affect decisions with regard to maintenance, repair/replacement, price setting, warranties, medical studies, and other areas. Most of the works containing the topics covered here are theoretical in nature. However, this book offers applications, exercises, and examples. It serves as a reference for professors and researchers involved in reliability and survival analysis.

Data-Driven Remaining Useful Life Prognosis Techniques
Data-Driven Remaining Useful Life Prognosis Techniques

Author: Xiao-Sheng Si

Publisher: Springer

Published: 2017-01-20

Total Pages: 436

ISBN-13: 3662540304

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This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans. It is also the first book that describes the basic data-driven remaining useful life prognosis theory systematically and in detail. The emphasis of the book is on the stochastic models, methods and applications employed in remaining useful life prognosis. It includes a wealth of degradation monitoring experiment data, practical prognosis methods for remaining useful life in various cases, and a series of applications incorporated into prognostic information in decision-making, such as maintenance-related decisions and ordering spare parts. It also highlights the latest advances in data-driven remaining useful life prognosis techniques, especially in the contexts of adaptive prognosis for linear stochastic degrading systems, nonlinear degradation modeling based prognosis, residual storage life prognosis, and prognostic information-based decision-making.