International conference supported by Indian Statistical Institute, held at Bangalore, 20-22 December, 2011; selected papers.

Engineering Reliability and Risk Assessment explains how to improve the performance of a system using the latest risk and reliability models. Against a backdrop of increasing availability of industrial data, and ever-increasing global commercial competition, the standards for optimal efficiency with minimum hazards keep improving. Topics explained include Effective strategies for the maintenance of the mechanical components of a system, How to schedule necessary interventions throughout the product life cycle, How to understand the structure and cost of complex systems, Planning a schedule to improve the reliability and life of the system, software, system safety and risk informed asset management, and more. - Uses case studies from industry practice to explain innovative solutions to real world risk assessment problems - Addresses the full interdisciplinary range of topics that influence this complex field - Provides brief introductions to important concepts, including risk and reliability analysis and fuzzy reliability

In an increasingly data-centric world, scholars and practitioners grapple with the complexities of harnessing data analytics effectively across various industries. The challenge lies in navigating the rapid evolution of methodologies, identifying emerging trends, and understanding the nuanced applications of data analytics in real-world scenarios. This gap between theory and practice inhibits academic progress. It hampers industry innovation, leaving stakeholders needing help to leverage data to its full potential. Recent Trends and Future Direction for Data Analytics presents a compelling solution. By delving into real-world case studies spanning supply chain management, marketing, healthcare, and finance, this book bridges the gap between theory and practice, offering invaluable insights into the practical applications of data analytics. A systematic exploration of fundamental concepts, advanced techniques, and specialized topics equips scholars, researchers, and industry professionals with the knowledge and tools needed to navigate the complexities of data analytics with confidence.

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 work illustrates research conducted over a ten-year timespan and addresses a fundamental issue in reliability theory. This still appears to be an empirically disorganized field and the book suggests employing a deductive base in order to evolve reliability as a science. The study is in line with the fundamental work by Gnedenko. Boris Vladimirovich Gnedenko (1912 – 1995) was a Soviet mathematician who made significant contributions in various scientific areas. His name is especially associated with studies of dependability, for which he is often recognized as the 'father' of reliability theory. In the last few decades, this area has expanded in new directions such as safety, security, risk analysis and other fields, yet the book ‘Mathematical Methods in Reliability Theory’ written by Gnedenko with Alexander Soloviev and Yuri Bélyaev still towers as a pillar of the reliability sector’s configuration and identity. The present book proceeds in the direction opened by the cultural project of the Russian authors; in particular it identifies different trends in the hazard rate functions by means of deductive logic and demonstrations. Further, it arrives at multiple results by means of the entropy function, an original mathematical tool in the reliability domain. As such, it will greatly benefit all specialists in the field who are interested in unconventional solutions.

Dependability and cost effectiveness are primarily seen as instruments for conducting international trade in the free market environment. These factors cannot be considered in isolation of each other. This handbook considers all aspects of performability engineering. The book provides a holistic view of the entire life cycle of activities of the product, along with the associated cost of environmental preservation at each stage, while maximizing the performance.

Over the last 50 years, the theory and the methods of reliability analysis have developed significantly. Therefore, it is very important to the reliability specialist to be informed of each reliability measure. This book will provide historical developments, current advancements, applications, numerous examples, and many case studies to bring the reader up-to-date with the advancements in this area. It covers reliability engineering in different branches, includes applications to reliability engineering practice, provides numerous examples to illustrate the theoretical results, and offers case studies along with real-world examples. This book is useful to engineering students, research scientist, and practitioners working in the field of reliability.

The aim of this book is to provide a platform to academicians, practitioners, and researchers to understand current and future trends in software reliability growth modeling. Emphasis will be on qualitative work relevant to the theme with particular importance given to mathematical modeling for software reliability and various methods and applications of multi attributed decision making in governing the software performance. Presents software quality and security models Offers reliability analysis, assurance techniques for software systems Covers methodologies, tools, and practical applications of software reliability modeling and testing resources Includes robust reliability design techniques, diagnostic, and decision support Discusses stochastic modelling for software systems

This book provides the latest research advances in the field of system reliability assurance and engineering. It contains reference material for applications of reliability in system engineering, offering a theoretical sound background with adequate numerical illustrations. Included are concepts pertaining to reliability analysis, assurance techniques and methodologies, tools, and practical applications of system reliability modeling and allocation. The collection discusses various soft computing techniques like artificial intelligence and particle swarm optimization approach for reliability assessment. Importance of differentiating between the optimal release time and testing stop time of the software has been explicitly discussed and presented in the book. Features: Creates understanding of the costs associated with complex systems Covers reliability measurement of engineering systems Incorporates an efficient effort-based expenditure policy incorporating cost and reliability criteria Provides information for optimal testing stop and release time of software system Presents software performance and security layout Addresses reliability prediction and its maintenance through advanced analytics techniques Overall, System Reliability Management: Solutions and Techniques is a collaborative and interdisciplinary approach for better communication of problems and solutions to increase the performance of the system for better utilization and resource management.