EMaintenance Essential Electronic Tools for Efficiency
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- Taschenbuch
- eBook ausgewählt
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Form:Einzelkauf Download
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Sprache:Englisch
160,00 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB 3
Kopierschutz
Nein
Family Sharing
Nein
Text-to-Speech
Ja
Erscheinungsdatum
15.06.2017
Verlag
Elsevier Science & Techn.Seitenzahl
552 (Printausgabe)
Sprache
Englisch
EAN
9780128111543
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
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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