
Optimization of Manufacturing Systems Using the Internet of Things
Academic Press
Erschienen am 21. Oktober 2016
Buch
Softcover
226 Seiten
978-0-12-809910-0 (ISBN)
Beschreibung
Optimization of Manufacturing Systems Using the Internet of Things extends the IoT (Internet of Things) into the manufacturing field to develop an IoMT (Internet of Manufacturing Things) architecture with real-time traceability, visibility, and interoperability in production planning, execution, and control. This book is essential reading for anyone interested in the optimization and control of an intelligent manufacturing system.
As modern manufacturing shop-floors can create bottlenecks in the capturing and collection of real-time field information, and because paper-based manual systems are time-consuming and prone to errors, this book helps readers understand how to alleviate these issues, assisting them in their decision-making on shop-floors.
As modern manufacturing shop-floors can create bottlenecks in the capturing and collection of real-time field information, and because paper-based manual systems are time-consuming and prone to errors, this book helps readers understand how to alleviate these issues, assisting them in their decision-making on shop-floors.
Weitere Details
Sprache
Englisch
Verlagsort
San Diego
USA
Verlagsgruppe
Elsevier Science Publishing Co Inc
Zielgruppe
Für Beruf und Forschung
Maße
Höhe: 229 mm
Breite: 152 mm
Gewicht
390 gr
ISBN-13
978-0-12-809910-0 (9780128099100)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
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Andere Ausgaben

Yingfeng Zhang | Fei Tao
Optimization of Manufacturing Systems Using the Internet of Things
E-Book
10/2016
Academic Press
108,00 €
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Personen
Yingfeng Zhang is a professor at the department of Industrial Engineering of the Northwestern Polytechnical University, China. Currently, his research interests are the Internet of Manufacturing Things (IoMT) and real-time data driven production optimization. Fei Tao is a Professor at the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. His research interests are service-oriented smart manufacturing, manufacturing service management and optimization, digital twin driven product design/manufacturing/service, green and sustainable manufacturing.
Autor*in
Northwestern Polytechnical University, China
Professor, School of Automation Science and Electrical Engineering, Beihang University, China
Inhalt
1. Introduction2. Overview of IoMT3. Real-time and multi-source manufacturing information perception4. IoT-enabled smart assembly station5. Cloud computing based manufacturing resources configuration method6. Real-time information-driven production-scheduling system7. IoT-enabled smart material handling8. Real-time key production performances monitor method9. IoMTprototype system10. Conclusions and future works