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Intelligent Prognostics for Engineering Systems with Machine Learning Techniques (Advanced Research in Reliability and System Assurance Engineering) - Softcover

 
9781032562971: Intelligent Prognostics for Engineering Systems with Machine Learning Techniques (Advanced Research in Reliability and System Assurance Engineering)

Synopsis

The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, electrical engineering, and computer science.

The book

  • Discusses basic as well as advance research in the field of prognostics
  • Explores integration of data collection, fault detection, degradation modeling and reliability prediction in one volume
  • Covers prognostics and health management (PHM) of engineering systems
  • Discusses latest approaches in the field of prognostics based on machine learning

The text deals with tools and techniques used to predict/ extrapolate/ forecast the process behavior, based on current health state assessment and future operating conditions with the help of Machine learning. It will serve as a useful reference text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, manufacturing science, electrical engineering, and computer science.

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About the Author

Gunjan Soni holds a BE from University of Rajasthan, MTech from IIT, Delhi, and PhD from Birla Institute of Technology and Science, Pilani, in 2012. He is presently working as an assistant professor in Department of Mechanical Engineering, Malaviya National Institute of Technology, Jaipur, Rajasthan, India. He has over 17 years of teaching experience at undergraduate and graduate levels. His areas of research interest are predictive maintenance and digital technology applications in supply chain management. He has published more than 80 papers in peer-reviewed journals including Journal of Business Research, Expert System with Applications, IEEE Transactions on Engineering Management, Production Planning and Control, Supply Chain Management: An International Journal, Annals of Operations Research, Computers and Industrial Engineering, International Journal of Logistics Research and Applications, etc. He is guest editor of special issues in journals like International Journal of Logistics Management, Sustainability, International Journal of Intelligent Enterprise, etc.

Om Prakash Yadav is a professor and Duin Endowed Fellow in the Department of Industrial and Manufacturing Engineering at North Dakota State University, Fargo. He holds a PhD in Industrial Engineering from Wayne State University, MS in Industrial Engineering from National Institute of Industrial Engineering Mumbai (India), and BS in Mechanical Engineering from Malaviya National Institute of Technology, Jaipur (India). His research interests include reliability modeling and analysis, risk assessment, design optimization, robust design, and manufacturing systems analysis. The research work of his group has been published in high-quality journals such as Reliability Engineering and Systems Safety, Journal of Risk and Reliability, Quality and Reliability Engineering International, and Engineering Management Journal. He has published over 130 papers in peer-reviewed journals and conference proceedings in the area of quality, reliability, product development, and operations management. Dr. Yadav is a recipient of the 2015 and 2018 IISE William A.J. Golomski best paper awards. He is currently a member of IISE, ASQ, SRE, and INFORMS.

Gaurav Kumar Badhotiya is currently an assistant professor in the Faculty of Management Studies, Marwadi University, Rajkot, Gujarat, India. He holds a PhD in Industrial Engineering and MTech in Manufacturing System Engineering from Malaviya National Institute of Technology, Jaipur, Rajasthan, India. His BTech is in Production and Industrial Engineering from the University College of Engineering, Kota, Rajasthan, India. Dr. Gaurav’s research interests are inclined toward areas in operations and supply chain management, such as supply chain resilience, production planning, circular economy, and sustainability. He has published more than 50 research articles in various peer-reviewed international journals, book chapters, and conferences proceedings. He is an editorial board member of International Journal of Mathematical, Engineering and Management Sciences. He has organized two Scopus Indexed International Conferences and a Faculty Development Program on Research Methodology and Data Analysis.

Mangey Ram holds a Ph.D. degree major in Mathematics and minor in Computer Science from G.B. Pant University of Agriculture and Technology, Pantnagar, India (2008). He is currently a research professor at Graphic Era (Deemed to be University), Dehradun, India, and a visiting professor at Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia. He is editor in chief of International Journal of Mathematical, Engineering and Management Sciences, Journal of Reliability and Statistical Studies, and 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, and River Publishers, and a guest editor and associate editor with various journals. He has published 300-plus publications (journal articles/books/book chapters/conference articles) in IEEE, Taylor & Francis, Springer Nature, Elsevier, Emerald, World Scientific, and many other national and international journals and conferences. Also, he has published more than 60 books (authored/edited) with international publishers like Elsevier, Springer Nature, CRC Press-A Taylor and Frances Group, Walter De Gruyter Publisher Germany, and River Publishers. His fields of research are reliability theory and applied mathematics. Dr. Ram is a senior member of the IEEE, senior life member of Operational Research Society of India, Society for Reliability Engineering, Quality and Operations Management in India, and Indian Society of Industrial and Applied Mathematics. He has been a member of the organizing committee of a number of international and national conferences, seminars, and workshops.

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9781032054360: Intelligent Prognostics for Engineering Systems with Machine Learning Techniques (Advanced Research in Reliability and System Assurance Engineering)

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Paperback. Condition: new. Paperback. The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, electrical engineering, and computer science.The bookDiscusses basic as well as advance research in the field of prognosticsExplores integration of data collection, fault detection, degradation modeling and reliability prediction in one volumeCovers prognostics and health management (PHM) of engineering systemsDiscusses latest approaches in the field of prognostics based on machine learningThe text deals with tools and techniques used to predict/ extrapolate/ forecast the process behavior, based on current health state assessment and future operating conditions with the help of Machine learning. It will serve as a useful reference text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, manufacturing science, electrical engineering, and computer science. The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781032562971

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