Search

This book discusses practical applications of reliability and statistical methods and techniques in various disciplines, using machine learning, artificial intelligence, optimization, and other computation methods. Bringing together research from international experts, each chapter aims to cover both methods and practical aspects on reliability or statistical computations with emphasis on applications. 5G and IoT are set to generate an estimated 1 billion terabytes of data by 2025 and companies continue to search for new techniques and tools that can help them practice data collection effectively in promoting their business. This book explores the era of big data through reliability and statistical computing, showcasing how almost all applications in our daily life have experienced a dramatic shift in the past two decades to a truly global industry. Including numerous illustrations and worked examples, the book is of interest to researchers, practicing engineers, and postgraduate students in the fields of reliability engineering, statistical computing, and machine learning.

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.

This book covers advanced reliability and maintainability knowledge as applied to recent engineering problems. It highlights research in the fields of reliability measures of binary and complex engineering systems, cost analysis, simulations, optimizations, risk factors, and sensitivity analysis. The book scrutinizes various advanced tools and techniques, methodology, and concepts to solve the various engineering problems related to reliability and maintainability of the industrial system at minimum cost and maximum profit. It consists of 15 chapters and offers a platform to researchers, academicians, professionals and scientists to enhance their knowledge and understanding the concept of reliability in engineering.

This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the author's recent research and publications as well as experience of over 30 years in this field. The book covers a wide range of methods and models in reliability, and their applications, including: statistical methods and model selection for machine learning; models for maintenance and software reliability; statistical reliability estimation of complex systems; and statistical reliability analysis of k out of n systems, standby systems and repairable systems. Offering numerous examples and solved problems within each chapter, this comprehensive text provides an introduction to reliability engineering graduate students, a reference for data scientists and reliability engineers, and a thorough guide for researchers and instructors in the field.

Integrating development processes, policies, and reliability predictions from the beginning of the product development lifecycle to ensure high levels of product performance and safety, this book helps companies overcome the challenges posed by increasingly complex systems in today's competitive marketplace. Examining both research on and practical aspects of product quality and reliability management with an emphasis on applications, the book features contributions written by active researchers and/or experienced practitioners in the field, so as to effectively bridge the gap between theory and practice and address new research challenges in reliability and quality management in practice. Postgraduates, researchers and practitioners in the areas of reliability engineering and management, amongst others, will find the book to offer a state-of-the-art survey of quality and reliability management and practices.

Software Reliability Assessment with OR Applications is a comprehensive guide to software reliability measurement, prediction, and control. It provides a thorough understanding of the field and gives solutions to the decision-making problems that concern software developers, engineers, practitioners, scientists, and researchers. Using operations research techniques, readers will learn how to solve problems under constraints such as cost, budget and schedules to achieve the highest possible quality level. Software Reliability Assessment with OR Applications is a comprehensive text on software engineering and applied statistics, state-of-the art software reliability modeling, techniques and methods for reliability assessment, and related optimization problems. It addresses various topics, including:unification methodologies in software reliability assessment; application of neural networks to software reliability assessment;software reliability growth modeling using stochastic differential equations;software release time and resource allocation problems; andoptimum component selection and reliability analysis for fault tolerant systems.Software Reliability Assessment with OR Applications is designed to cater to the needs of software engineering practitioners, developers, security or risk managers, and statisticians. It can also be used as a textbook for advanced undergraduate or postgraduate courses in software reliability, industrial engineering, and operations research and management.

This book aims to present a state-of-the-art survey of theories and methods of reliability, maintenance, and warranty with emphasis on multi-unit systems, and to reflect current hot topics: imperfect maintenance, economic dependence, opportunistic maintenance, quasi-renewal processes, warranty with maintenance and economic dependency, and software testing and maintenance. This book is distinct from others because it consists mainly of research work published on technical journals and conferences in recent years by us and our co-authors. Maintenance involves preventive and unplanned actions carried out to retain a system at or restore it to an acceptable operating condition. Optimal maintenance policies aim to provide optimum system reliability and safety performance at the lowest possible maintenance costs. Proper maintenance techniques have been emphasized in recent years due to increased safety and reliability requirements of systems, increased complexity, and rising costs of material and labor. For some systems, such as aircraft, submarines, and nuclear power stations, it is extremely important to avoid failure during actual operation because it is dangerous and disastrous.