Case Studies in Digital Transformation : Integration of Digital Technologies to Enhance Asset Management Processes

This book is exploration into the forefront of digital evolution, presenting a compelling array of real-world case studies that underscore the transformative impact of emerging processes and services on asset management. The book goes beyond theoretical frameworks, offering a dynamic narrative that reveals how organizations across industries are strategically integrating cutting-edge technologies into their asset management practices.

With a keen focus on innovation, the book examines the key role of IoT, artificial intelligence, and other groundbreaking technologies in reshaping traditional asset management paradigms. Readers will gain valuable insights into success stories, challenges faced, and the strategic considerations that underpin these transformative journeys. The book's coverage highlights the tangible benefits of digital solutions, such as enhanced efficiency, heightened resilience, and strategic advantage.

Adolfo Crespo Márquez is a Full Professor at the University of Seville with more than 25 years in asset and maintenance management. He received the Spanish Maintenance Award (AEM, 2020) and is listed in Stanford University’s world top-scientists ranking (since 2022). Author of The Maintenance Management Framework (Springer, 2007) and several other books, his models have been applied across utilities and industry in Europe the Americas and the Middle East. He is Editor-in-Chief of the Engineering Asset Management Review series, a Fellow and Director of ISEAM, and President of INGEMAN. His research focuses on digital transformation, reliability, and strategic asset management for industrial and infrastructure systems.

Turuna Seecharan is an Associate Professor in the Department of Mechanical and Industrial Engineering at the University of Minnesota Duluth. She is a licensed Professional Engineer with the Professional Engineers of Ontario and a board member of the International Society of Engineering Asset Management. Her research interests are Gamification and the role of Human Factors in Asset Management.

Dr. Georges Abdul-Nour is an Emeritus Professor of Industrial engineering, Université du Québec, Canada. He completed his PhD at Texas Tech University. He authored and co-authored more than 450 books and chapters, refereed papers, and technical reports. His research interest is in Intelligent Asset Management, Systems Resilience, and Reliability, Lean Intelligent Manufacturing and Six Sigma. He is member of the Editorial Board of International Journal of Production Research, and Director on the Board of International Society of Engineering Asset Management. He is an Elected Member of the Academy of Industrial Engineering of Texas Tech. He is a Fellow of ISEAM.

Joe Amadi-Echendu is Emeritus Professor of Engineering and Technology Management at the University of Pretoria, South Africa.  Professor Amadi-Echendu is the founding Editor-in-Chief of EAMR Series.  He is the sole author of a textbook, lead author of 3 books, and co-editor of another 7 books all published by Springer. Joe is registered as a chartered professional engineer in the UK and South Africa and currently serves as the Chair of Board of Directors of the International Society of Engineering Asset Management.

Jay Lee is Clark Distinguished Chair Professor and Director of the Industrial AI Center at the University of Maryland, College Park. He is internationally recognized for his pioneering contributions to industrial AI and intelligent maintenance systems. Formerly, he was Ohio Eminent Scholar, L.W. Scott Alter Chair, and University Distinguished Professor at the University of Cincinnati. Dr. Lee founded the NSF I/UCRC on Intelligent Maintenance Systems and has led major collaborations with global industry partners. His leadership has had significant economic and technological impact. As Founding Director of the Industrial AI Center, he remains at the forefront of advancing smart manufacturing and predictive analytics in asset management.