Reliability Modeling in Industry 4.0 (Advances in Reliability Science) - Softcover

Über die Autorinnen und Autoren

Prof. Mangey Ram is Professor at Graphic Era (Deemed to be University), Dehradun, India. He is Editor-in-Chief of the International Journal of Mathematical, Engineering, and Management Sciences; Journal of Reliability and Statistical Studies; Journal of Graphic Era University; Series Editor of six book series with Elsevier, CRC Press-A Taylor and Frances Group, Walter De Gruyter Publisher Germany, River Publisher and Guest Editor and Associate Editor for various journals. His fields of research are reliability theory and applied mathematics.

He is Editor-in-Chief of the International Journal of Mathematical, Engineering, and Management Sciences; Journal of Reliability and Statistical Studies; Journal of Graphic Era University; Series Editor of six book series with Elsevier, CRC Press-A Taylor and Frances Group, Walter De Gruyter Publisher Germany, River Publisher and Guest Editor and Associate Editor for various journals.

His fields of research are reliability theory and applied mathematics.

Prof. Ram is a Senior Member of the IEEE, Senior Life Member of the Operational Research Society of India, the Society for Reliability Engineering, Quality and Operations Management in India, the Indian Society of Industrial and Applied Mathematics. He is a member of the organizing committee of several international and national conferences, seminars, and workshops. He was conferred the “Young Scientist Award” by the Uttarakhand State Council for Science and Technology, Dehradun, in 2009, and given the “Best Faculty Award” in 2011; “Research Excellence Award” in 2015; and “Outstanding Researcher Award” in 2018 for his significant contributions in academics and research at Graphic Era (deemed to be University), Dehradun, India. Most recently, he received the "Excellence in Research of the Year-2021 Award” from the Honourable Chief Minister of the Uttarakhand State, India.

Liudong Xing is currently a professor at the Department of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, United States. Her research interests include reliability and resilience modeling, analysis, and optimization of complex systems and networks (e.g., IoT and wireless sensor networks). Prof. Xing has received multiple teaching and scholar awards and was corecipient of the Best (Student) Paper Award at several international conferences and journals. She has published over 290 journal articles, and 2 books titled Binary Decision Diagrams and Extensions for System Reliability Analysis and Dynamic System Reliability: Modeling and Analysis of Dynamic and Dependent Behaviors. She has served as an associate editor or editorial board member of multiple journals, including Reliability Engineering & System Safety, IEEE Internet of Things Journal, IEEE Access, and International Journal of Mathematical, Engineering and Management Sciences. She is a fellow of the International Society of Engineering Asset Management and a senior member of IEEE.

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Reliability Modeling with Industry 4.0 explores the emerging theoretical and practical developments in reliability engineering in highly digitized industries including power, computer systems, railway systems, and robotics.

The reliability of a system affects performance indices including production costs, maintenance and management costs, and product quality, making it a priority for many professionals. The increasing complexity in data collection and analysis caused by the industry 4.0 revolution presents reliability engineers with a classic challenge vs opportunity situation, where traditional methods are no longer effective but the successful integration and analysis of data across systems promises great improvements.

Drawing on leading research from around the globe, as well as the latest in industry practice, this book provides cutting edge advice on how to integrate a fully digitized industry 4.0 system for enhanced reliability and reduced maintenance cost. Technologies such as big data, artificial intelligence, and the industrial internet of things are addressed in the context of reliability engineering, providing practical advice on applications.