This book presents the latest research in the fields of reliability theory and its applications, providing a comprehensive overview of reliability engineering and discussing various tools, techniques, strategies and methods within these areas. Reliability analysis is one of the most multidimensional topics in the field of systems reliability engineering, and while its rapid development creates opportunities for industrialists and academics, it is also means that it is hard to keep up to date with the research taking place. By gathering findings from institutions around the globe, the book offers insights into the international developments in the field. As well as discussing the current areas of research, it also identifies knowledge gaps in reliability theory and its applications and highlights fruitful avenues for future research. Covering topics from life cycle sustainability to performance analysis of cloud computing, this book is ideal for upper undergraduate and postgraduate researchers studying reliability engineering.

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.

New, global and extended markets are forcing companies to process and manage increasingly differentiated products with shorter life cycles, low volumes and reduced customer delivery times. In today's global marketplace production systems need to be able to deliver products on time, maintain market credibility and introduce new products and services faster than competitors. As a result, a new production paradigm of a production system has been developed and a supporting management decision-making approach simultaneously incorporating design, management, and control of the production system is necessary so that this challenge can be effectively and efficiency met. "Maintenance Engineering and its Applications in Production Systems" meets this need by introducing an original and integrated idea of maintenance: maintenance for productivity. The volume starts with the introduction and discussion of a new conceptual framework based on productivity, quality, and safety supported by maintenance. Subsequent chapters illustrate the most relevant models and methods to plan, organise, implement and control the whole maintenance process (reliability evaluation models and prediction, maintenance strategies and policies, spare parts management, computer maintenance management software - CMMS, and total productive maintenance - TPM, etc.). Several examples of problems supported by solutions, and real applications to help and test the reader's comprehension are included. "Maintenance Engineering and its Applications in Production Systems" will certainly be valuable to engineering students, doctoral and post-doctoral students and also to maintenance practitioners, as well as managers of industrial and service companies.

Computer software reliability has never been more important. Today, computers are employed in areas as diverse as air traffic control, nuclear reactors, aircraft, real-time military, industrial process control, security system control, biometric scan-systems, automotive, mechanical and safety control, and hospital patient monitoring systems. Many of these applications require critical functionality as software applications increase in size and complexity.

System Software Reliability is an introduction to software reliability engineering as well as a detailed survey of the state-of-the-art techniques, methodologies and tools used to assess the reliability of software and combined software-hardware systems. The most recent research results in the field are reported and future directions in the subject are signposted.

This comprehensive text will be of interest to:

• graduate students as an introduction to software reliability engineering and a textbook for graduate courses;
• software and reliability engineers as a comprehensive and up-to-date survey of the field; and,
• researchers and lecturers in universities and research institutions as a one-volume reference.

For some systems, such as aircraft, submarines, military systems and aerospace systems, it is extremely important to avoid failure during actual operation because it is dangerous and disastrous. The study of various maintenance policies and models in order to improve system reliability, to prevent the occurrence of system failure, and to reduce maintenance costs is an important area in reliability engineering. Proper maintenance techniques have been emphasized in recent years due to the increased safety and reliability requirements of systems, and the increased complexity and rising costs of material and labor.

Based on the authorsa (TM) research, Reliability and Optimal Maintenance presents the latest theories and methods of reliability and maintenance with an emphasis on multi-component systems, while also considering the current hot topics in reliability and maintenance including: imperfect repair, economic dependence and opportunistic maintenance, and correlated failure and repair. Software reliability and maintenance cost, and warranty cost considerations are also considered.

Postgraduates, researchers, and practitioners in reliability engineering, maintenance engineering, operations research, industrial engineering, mechanical engineering, logistics, management, and statistics will find this book a state-of-the-art survey of reliability and maintenance theory and models.

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 presents the latest theories and methods of reliability and quality, with emphasis on reliability and quality in design and modelling. Each chapter is written by active researchers and professionals with international reputations, providing material which bridges the gap between theory and practice to trigger new practices and research challenges. The book therefore provides a state-of-the-art survey of reliability and quality in design 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; and optimum 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 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.

The book begins with an introduction to software reliability, models and techniques. The book is an informative book covering the strategies needed to assess software failure behaviour and its quality, as well as the application of optimization tools for major managerial decisions related to the software development process. It features a broad range of topics including software reliability assessment and apportionment, optimal allocation and selection decisions and upgradations problems. It moves through a variety of problems related to the evolving field of optimization of software reliability engineering, including software release time, resource allocating, budget planning and warranty models, which are each explored in depth in dedicated chapters. This book provides a comprehensive insight into present-day practices in software reliability engineering, making it relevant to students, researchers, academics and practising consultants and engineers.

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.

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 latest research in the fields of reliability theory and its applications, providing a comprehensive overview of reliability engineering and discussing various tools, techniques, strategies and methods within these areas. Reliability analysis is one of the most multidimensional topics in the field of systems reliability engineering, and while its rapid development creates opportunities for industrialists and academics, it is also means that it is hard to keep up to date with the research taking place. By gathering findings from institutions around the globe, the book offers insights into the international developments in the field. As well as discussing the current areas of research, it also identifies knowledge gaps in reliability theory and its applications and highlights fruitful avenues for future research. Covering topics from life cycle sustainability to performance analysis of cloud computing, this book is ideal for upper undergraduate and postgraduate researchers studying reliability engineering.

Safety and Reliability Modeling and Its Applications combines work by leading researchers in engineering, statistics and mathematics who provide innovative methods and solutions for this fast-moving field. Safety and reliability analysis is one of the most multidimensional topics in engineering today. Its rapid development has created many opportunities and challenges for both industrialists and academics, while also completely changing the global design and systems engineering environment. As more modeling tasks can now be undertaken within a computer environment using simulation and virtual reality technologies, this book helps readers understand the number and variety of research studies focusing on this important topic. The book addresses these important recent developments, presenting new theoretical issues that were not previously presented in the literature, along with solutions to important practical problems and case studies that illustrate how to apply the methodology.

This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems. Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.

The two-volume set LNAI 10751 and 10752 constitutes the refereed proceedings of the 10th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2018, held in Dong Hoi City, Vietnam, in March 2018. The total of 133 full papers accepted for publication in these proceedings was carefully reviewed and selected from 423 submissions. They were organized in topical sections named: Knowledge Engineering and Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Machine Learning and Data Mining; Decision Support and Control Systems; Computer Vision Techniques; Advanced Data Mining Techniques and Applications; Multiple Model Approach to Machine Learning; Sensor Networks and Internet of Things; Intelligent Information Systems; Data Structures Modeling for Knowledge Representation; Modeling, Storing, and Querying of Graph Data; Data Science and Computational Intelligence; Design Thinking Based R&D, Development Technique, and Project Based Learning; Intelligent and Contextual Systems; Intelligent Systems and Algorithms in Information Sciences; Intelligent Applications of Internet of Thing and Data Analysis Technologies; Intelligent Systems and Methods in Biomedicine; Intelligent Biomarkers of Neurodegenerative Processes in Brain; Analysis of Image, Video and Motion Data in Life Sciences; Computational Imaging and Vision; Computer Vision and Robotics; Intelligent Computer Vision Systems and Applications; Intelligent Systems for Optimization of Logistics and Industrial Applications.

The two-volume set LNAI 10751 and 10752 constitutes the refereed proceedings of the 10th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2018, held in Dong Hoi City, Vietnam, in March 2018. The total of 133 full papers accepted for publication in these proceedings was carefully reviewed and selected from 423 submissions. They were organized in topical sections named: Knowledge Engineering and Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Machine Learning and Data Mining; Decision Support and Control Systems; Computer Vision Techniques; Advanced Data Mining Techniques and Applications; Multiple Model Approach to Machine Learning; Sensor Networks and Internet of Things; Intelligent Information Systems; Data Structures Modeling for Knowledge Representation; Modeling, Storing, and Querying of Graph Data; Data Science and Computational Intelligence; Design Thinking Based R&D, Development Technique, and Project Based Learning; Intelligent and Contextual Systems; Intelligent Systems and Algorithms in Information Sciences; Intelligent Applications of Internet of Thing and Data Analysis Technologies; Intelligent Systems and Methods in Biomedicine; Intelligent Biomarkers of Neurodegenerative Processes in Brain; Analysis of Image, Video and Motion Data in Life Sciences; Computational Imaging and Vision; Computer Vision and Robotics; Intelligent Computer Vision Systems and Applications; Intelligent Systems for Optimization of Logistics and Industrial Applications.

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.

An effective reliability programme is an essential component of every product's design, testing and efficient production. From the failure analysis of a microelectronic device to software fault tolerance and from the accelerated life testing of mechanical components to hardware verification, a common underlying philosophy of reliability applies. Defining both fundamental and applied work across the entire systems reliability arena, this state-of-the-art reference presents methodologies for quality, maintainability and dependability. Featuring: Contributions from 60 leading reliability experts in academia and industry giving comprehensive and authoritative coverage. A distinguished international Editorial Board ensuring clarity and precision throughout. Extensive references to the theoretical foundations, recent research and future directions described in each chapter. Comprehensive subject index providing maximum utility to the reader. Applications and examples across all branches of engineering including IT, power, automotive and aerospace sectors. The handbook's cross-disciplinary scope will ensure that it serves as an indispensable tool for researchers in industrial, electrical, electronics, computer, civil, mechanical and systems engineering. It will also aid professional engineers to find creative reliability solutions and management to evaluate systems reliability and to improve processes. For student research projects it will be the ideal starting point whether addressing basic questions in communications and electronics or learning advanced applications in micro-electro-mechanical systems (MEMS), manufacturing and high-assurance engineering systems.

Safety and Risk Modeling presents the latest theories and methods of safety and risk with an emphasis on safety and risk in modeling. It covers applications in several areas including transportations and security risk assessments, as well as applications related to current topics in safety and risk. Safety and Risk Modeling is a valuable resource for understanding the latest developments in both qualitative and quantitative methods of safety and risk analysis and their applications in operating environments. Each chapter has been written by active researchers or experienced practitioners to bridge the gap between theory and practice and to trigger new research challenges in safety and risk. Topics include: safety engineering, system maintenance, safety in design, failure analysis, and risk concept and modelling. Postgraduate students, researchers, and practitioners in many fields of engineering, operations research, management, and statistics will find Safety and Risk Modeling a state-of-the-art survey of reliability and quality in design and practice.

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; and optimum 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.

Based on the authors research, Reliability and Optimal Maintenance presents the latest theories and methods of reliability and maintenance with an emphasis on multi-component systems, while also considering current hot topics in reliability and maintenance including: imperfect repair, economic dependence and opportunistic maintenance, and correlated failure and repair. Software reliability and maintenance cost, and warranty cost considerations are also considered.

Computer software reliability has never been so important. Computers are used in areas as diverse as air traffic control, nuclear reactors, real-time military, industrial process control, security system control, biometric scan-systems, automotive, mechanical and safety control, and hospital patient monitoring systems. Many of these applications require critical functionality as software applications increase in size and complexity. This book is an introduction to software reliability engineering and a survey of the state-of-the-art techniques, methodologies and tools used to assess the reliability of software and combined software-hardware systems. Current research results are reported and future directions are signposted. This text will interest: graduate students as a course textbook introducing reliability engineering software; reliability engineers as a broad, up-to-date survey of the field; and researchers and lecturers in universities and research institutions as a one-volume reference.

"Recent Advances in Reliability and Quality in Design" presents the latest theories and methods of reliability and quality, with emphasis on reliability and quality in design and modelling. Each chapter is written by active researchers and professionals with international reputations, providing material which bridges the gap between theory and practice to trigger new practices and research challenges.

Postgraduates, researchers, and practitioners in reliability engineering, maintenance engineering, quality engineering, operations research, industrial and systems engineering, mechanical engineering, computer engineering, management, and statistics will find this book a state-of-the-art survey of reliability and quality in design and practices.

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.