Diego Galar, Uday Kumar

eMaintenance (eBook, ePUB)

Essential Electronic Tools for Efficiency

• Format: ePub

Produktbeschreibung

eMaintenance: Essential Electronic Tools for Efficiency enables the reader to improve efficiency of operations, maintenance staff, infrastructure managers and system integrators, by accessing a real time computerized system from data to decision. In recent years, the exciting possibilities of eMaintenance have become increasingly recognized as a source of productivity improvement in industry. The seamless linking of systems and equipment to control centres for real time reconfiguring is improving efficiency, reliability, and sustainability in a variety of settings.

The book provides an introduction to collecting and processing data from machinery, explains the methods of overcoming the challenges of data collection and processing, and presents tools for data driven condition monitoring and decision making. This is a groundbreaking handbook for those interested in the possibilities of running a plant as a smart asset.

• Provides an introduction to collecting and processing data from machinery
• Explains how to use sensor-based tools to increase efficiency of diagnosis, prognosis, and decision-making in maintenance
• Describes methods for overcoming the challenges of data collection and processing

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 552
• Erscheinungstermin: 15. Juni 2017
• Englisch
• ISBN-13: 9780128111543
• Artikelnr.: 48497210

Autorenporträt

Diego Galar is Professor of Condition Monitoring in the Division of Operation and Maintenance Engineering at LTU, Luleå University of Technology where he is coordinating several H2020 projects related to different aspects of cyber physical systems, Industry 4.0, IoT or industrial Big Data. He was also involved in the SKF UTC centre located in Lulea focused on SMART bearings, and is actively involved in national projects within the Swedish industry. Dr. Galar is principal researcher at Tecnalia, in Spain, heading the Maintenance and Reliability research group. He has authored more than 300 journal and conference papers, books and technical reports in the field of maintenance, working as member of editorial boards, scientific committees and chairing international journals and conferences. In industry, he has been technological director and CBM manager of international companies, and actively participated in national and international committees for standardization and R&D in the topics of reliability and maintenance. In the international arena, he has been visiting Professor in the Polytechnic of Braganza (Portugal), University of Valencia and NIU (USA). Currently, he is visiting Professor at the University of Sunderland (UK) and University of Maryland (USA), as well as guest Professor at the Pontificia Universidad Católica de Chile.Uday Kumar is professor of operation and maintenance engineering, director of Luleå Railway Research Center and scientific director of the Strategic Area of Research and Innovation-Sustainable Transport at Luleå University of Technology, Luleå, Sweden. Before joining Luleå University of Technology, Dr. Kumar was professor of Offshore Technology (Operation and Maintenance Engineering) at Stavanger University, Norway. Dr. Kumar has research interests in the subject area of reliability and maintainability engineering, maintenance modeling, condition monitoring, LCC and risk analysis, etc. He has published more than 300 papers in international jour- nals and peer-reviewed conferences and has made contributions to many edited books. He has supervised more than 25 PhD theses related to the area of reliability and maintenance. Dr. Kumar has been a keynote and invited speaker at numerous congresses, conferences, seminars, industrial forums, workshops, and academic institutions. He is an elected member of the Swedish Royal Academy of Engineering Sciences.

Inhaltsangabe

1. Sensors and Data Acquisition2. Data Collection3. Preprocessing and Features4. Data and Information Fusion From Disparate Asset Management Sources5. Diagnosis6. Prognosis7. Maintenance Decision Support Systems8. Actuators and Self-Maintenance Approaches