Stochastic Reliability Modeling Optimization And Applications

"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." "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." --Book Jacket.

Reliability modeling has been a major concern for engineers and managers engaged in high quality system designs. This book presents the recent advancement in reliability theory and reliability engineering. Starting from maintenance policies, the book introduces reliability analysis to systems using stochastic processes to study their optimization problems. In this book, the authors will illustrate how these techniques of reliability are applied to solve optimization problems in computer, information and network systems. Contents:Maintenance Policies:A Dynamic Programming Approach for Sequential Preventive Maintenance Policies with Two Failure Modes (Hiroyuki Okamura, Tadashi Dohi and Shunji Osaki)Selective Maintenance for Complex Systems Considering Imperfect Maintenance Efficiency (Mayank Pandey, Yu Liu, Ming J Zuo)Random Replacement Policies (Won Young Yun and Li Liu)Optimal Replacement Interval of a Dual System (Satoshi Mizutani)Cumulative Damage Models with Random Working Times (Xufeng Zhao, Cunhua Qian and Shey-Huei Sheu)Reliability Analysis:Modules of Multi-State Coherent Systems — Order Theoretical Relations (Fumio Ohi)Calculation Algorithms for the System State Distributions of Multi-State k-out-of-n Systems (Hisahi Yamamoto and Tomoaki Akiba)Multi-state Components Assignment Problem with Optimal Network Reliability Subject to Assignment Budget (Yi-Kuei Lin and Cheng-Ta Yeh)Reliability Analysis of a Server System with Replication Schemes (Mitsutaka Kimura)Computer Systems:Two-Dimensional Software Reliability Growth Models (Shinji Inoue and Shigeru Yamada)Hybrid Coordinated Checkpointing Technique Using Incremental Snapshots (Mamoru Ohara, Masayuki Arai, Satoshi Fukumoto and Kazuhiko Iwasaki)Predicting Effort and Errors for Embedded Software Development Projects by Using an Artificial Neural Network (Kazunori Iwata, Sayori Maeji and Toshio Nakagawa)Optimal Checkpoint Times for Database Systems (Kenichiro Naruse and Sayori Maeji)Periodic and Random Inspections for a Computer System (Mingchih Chen, Xufeng Zhao and Syouji Nakamura)Reliability Applications:Dynamic Fault Tree Analysis (Tetsushi Yuge and Shigeru Yanagi)Reliability Analysis and Modeling Technique for an Open Source Solution (Yoshinobu Tamura and Shigeru Yamada)Maintenance Models of Miscellaneous Systems (Kodo Ito)Reliability Analysis of a System Connected with the Radio Link (Mitsuhiro Imaizumi)Studies on Reliability and Maintenance:Studies on Reliability and Maintenance (Toshio Nakagawa) Readership: Undergraduates and postgraduate students, researchers and designers in the areas of optimization, mathematical modeling, stochastic analysis and industrial engineering. Keywords:Reliability;Maintenance;Optimization;Stochastic;Probability;Modeling;Damage;Computer

Aims to survey research topics in reliability theory and useful applied techniques in reliability engineering. This book focuses 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.

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.

This books covers the broad range of research in stochastic models and optimization. Applications presented include networks, financial engineering, production planning, and supply chain management. Each contribution is aimed at graduate students working in operations research, probability, and statistics.

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.