Springer Reliability Engineering for Industrial Processes: An Analytics Perspective (Springer Series in Reliability Engineering)

This book explores how transformative changes driven by the new-age economy can bring about improvements in a company's engineering and manufacturing capabilities. The new-age economy is driven by advanced engineering and manufacturing practices, processes, and technologies, including the Internet of Things (IoT), Cloud Computing, Blockchain, Artificial Intelligence, Robotics, Cyber-Physical Systems (CPS), and Internet-enabled systems to automate industrial processes. Today's business dynamics are governed by uncertainties, disruptions, complexities, and ambiguities that demand quicker and more intelligent decisions. These changes could relate a renaissance in the company's engineering and manufacturing capabilities. To sustain these volatile and ever-changing business dynamics, Industry 4.0 and 5.0 have revolutionized how organizations operate and make intelligent business decisions. Moreover, the extensive role of business analytics has overcome the limitations ofclassical computing through new technologies and intelligent computing methodologies. Over the past few years, much emphasis has been given to investing in developing hardware and programming frameworks for achieving computational intelligence using fuzzy logic, evolutionary computation, neural networks, probabilistic methods, and learning theory. Within this frame of reference, the reliability, quality, and maintenance of complex industrial and manufacturing systems are essential for organizations to utilize them successfully for informed decisions. This book focuses on studies that provide new solutions for system reliability, quality, security, and maintainability using quantitative and qualitative research. It emphasizes developments and problems in systems engineering management, systems integration, software and hardware engineering, and the development process.