Advances in Reliability Science – serie

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.

Reliability Analysis and Asset Management of Engineering Systems explains methods that can be used to evaluate reliability and availability of complex systems, including simulation-based methods.

The increasing digitization of mechanical processes driven by Industry 4.0 increases the interaction between machines and monitoring and control systems, leading to increases in system complexity. For those systems the reliability and availability analyses are increasingly challenging, as the interaction between machines has become more complex, and the analysis of the flexibility of the production systems to respond to machinery failure may require advanced simulation techniques.

This book fills a gap on how to deal with such complex systems by linking the concepts of systems reliability and asset management, and then making these solutions more accessible to industry by explaining the availability analysis of complex systems based on simulation methods that emphasise Petri nets.

Modern systems have become increasingly complex to design and build, while the demand for reliability and cost-effective enhancement continues. Robust international competition has further intensified the need for all designers, managers, practitioners, scientists, and engineers to ensure a level of reliability of their products and processes before release at the lowest cost.Developments in Reliability Engineering equips its audience with the necessary information to keep up with the latest original research and state-of-the-art advances in reliability engineering. The volume offers an excursus from historical theories and methods to the present-world practical utility of these concepts with worked-out examples.

Reliability and Resilience in the Internet of Things explains the latest advances in reliability and resilience modeling, analysis, and design techniques for Internet of Things (IoT) systems. Over the last decade, IoT has developed rapidly, and it now spans diverse application domains such as healthcare, home automation, smart manufacturing, smart ocean, and smart agriculture. Due to the critical nature of these applications, it is imperative that the IoT systems operate reliably throughout the intended mission time. This timely book provides state-of the-art coverage on IoT reliability and resilience modeling, analysis, and design methods and solutions to help prevent costly malfunctions. From the viewpoint of engineers, researchers, and developers, reliability analysis and resilience design are key to the deployment and operation of IoT systems in critical applications, and this book contains the best advice on the subject available. It is a valuable resource for researchers in academia and industry interested in smart IoT systems and Industry 4.0.

Dynamic Modelling of Time-to-Event Processes covers an alternative dynamic modelling approach for studying time-to-event processes. This innovative approach covers some key elements, including the Development of continuous-time state of dynamic time-to-event processes, an Introduction of an idea of discrete-time dynamic intervention processes, Treating a time-to-event process operating/functioning under multiple time-scales formulation of continuous and discrete-time interconnected dynamic system as hybrid dynamic time-to-event process, Utilizing Euler-type discretized schemes, developing theoretical dynamic algorithms, and more.Additional elements of this process include an Introduction of conceptual and computational state and parameter estimation procedures, Developing multistage a robust mean square suboptimal criterion for state and parameter estimation, and Extending the idea conceptual computational simulation process and applying real datasets.

Risk, Reliability and Resilience in Operations Management examines measurement tools and techniques and their real-world application. The book provides a resource that is needed to help solve complex business operations and global supply chains and their important requirements for the accurate measurement of risk, reliability, and resilience to inform decisions and reduce risk. In addition, the book discusses advancements in technology and data analytics, with final sections covering the COVID-19 pandemic and how it has put greater emphasis on the importance of risk, reliability, and resilience in business operations.This book provides a timely overview of measurement techniques and their application in operations management, offering insights into future directions in this field.