Value Based and Intelligent Asset Management

Crespo Márquez, Adolfo|Macchi, Marco|Parlikad, Ajith Kumar

ISBN 10: 3030207064 / ISBN 13: 9783030207069

Published by Springer International Publishing, 2020

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces asset management and intelligent asset management systemsDescribes how asset management is being transformed in the digital eraProvides practical methods that can be applied in business and industry.

Seller Inventory # 448675218

Bibliographic Details

• Title: Value Based and Intelligent Asset Management
• Publisher: Springer International Publishing
• Publication Date: 2020
• Language: English
• ISBN 10: 3030207064
• ISBN 13: 9783030207069
• Binding: Soft cover
• Condition: New
• Seller catalogs:
  • Mathematik/Naturwissenschaften/Technik/Medizin

About this title

Synopsis

The fundamental motivation of this book is to contribute to the future advancement of Asset Management in the context of industrial plants and infrastructures. The book aims to foster a future perspective that takes advantage of value-based and intelligent asset management in order to make a step forward with respect to the evolution observed nowadays. Indeed, the current understanding of asset management is primarily supported by well-known standards. Nonetheless, asset management is still a young discipline and the knowledge developed by industry and academia is not set in stone yet. Furthermore, current trends in new organizational concepts and technologies lead to an evolutionary path in the field. Therefore, this book aims to discuss this evolutionary path, starting first of all from the consolidated theory, then moving forward to discuss:

• The strategic understanding of value-based asset management in a company;

• An operational definition ofvalue, as a concept on the background of value-based asset management;

• The identification of intelligent asset management, with the aim to frame a set of “tools” recommended to support the asset-related decision-making process over the asset lifecycle;

• The emergence of new technologies such as cyber physical systems and digital twins, and the implications of this on asset management.

About the Author

Adolfo Crespo Márquez is currently Full Professor at the School of Engineering of the University of Seville, and Head of the Department of Industrial Management. He holds a Ph.D. with Honors in Industrial Engineering from this same University. His research works have been published in journals such as Reliability Engineering and System Safety, International Journal of Production Research, International Journal of Production Economics, European Journal of Operations Research, Omega, Decision Support Systems and Computers in Industry, among others. Prof. Crespo is the author of nine books, the last six with Springer-Verlag (2007, 2010, 2012, 2014 & 2017) and Aenor (2016) about maintenance, warranty, supply chain and asset management. Professor Crespo is Fellow of ISEAM (International Society of Engineering Asset management) and leads the Spanish Research Network on Asset management and the Spanish Committee for Maintenance Standardization (1995–2003). He also leads the SIM (Sistemas Inteligentes de Mantenimiento) research group related to maintenance and dependability management and has extensively participated in many engineering and consulting projects for different companies, for the Spanish Departments of Defense, Science and Education as well as for the European Commission (IPTS). He is the President of INGEMAN (a National Association for the Development of Maintenance Engineering in Spain) since 2002.

 

Marco Macchi is currently Full Professor at Department of Management, Economics and Industrial Engineering of Politecnico di Milano. His teaching activity is in the area of production systems, industrial technologies, asset lifecycle management, operations and maintenance management, both to undergraduate and postgraduate students; he also regularly teaches for the doctorate program in Management Engineering, in the area of modeling and simulation of complex systems. His research interests are focused on several topicsconcerning asset and operations management within engineered systems. He is author or co-author of 4 books and more than 100 papers at national and international levels. Serving to the scientific community, he is currently Vice-chair of the IFAC (Int. Federation for Automatic Control) TC (technical committee) 5.1 Manufacturing Plant Control, and Chair of the IFAC Working Group A-MEST (Advanced Maintenance Engineering, Services and Technology), WG affiliated to the IFAC TC 5.1 Manufacturing Plant Control; he is Member of the IFIP (Int. Federation for Information Processing) WG 5.7 Advances in Production Management Systems and the IFAC TC 5.3 Enterprise Integration and Networking; besides, he is Book Reviews Editor and Editorial Board Member of the International Journal Production Planning & Control: The Management of Operations, Taylor & Francis.

 

Ajith Kumar Parlikad is Senior Lecturer in Industrial Systems at Cambridge University Engineering Department (CUED). He is the head of the Asset Management Group at the Institute for Manufacturing and a Co-Investigator for the Centre for Smart Infrastructure and Construction and the Centre for Digital Built Britain. His research focusses on examining how asset information can effectively be managed and used to improve asset investment and maintenance decision-making. He is author or co-author of 2 books and has published more than 100 papers in peer-reviewed international journals and conference proceedings. His research has been funded by the UK Government, EU H2020 and Industry. Dr Parlikad sits on the steering committee of the IFAC Working Group on Advanced Maintenance Engineering, Services and Technology and is a member of the Management Advisory Board for the Centre for Digital Built Britain. Dr Parlikad's current research focusses on the development of infrastructure digital twins and how data from disparate sources such as BIM models and condition-monitoring and sensing technologies can be integrated and brought to bear to improve asset management.