Springer Series in Advanced Manufacturing
2006
Condition Monitoring and Control for Intelligent Manufacturing Editors:

• Lihui Wang Ph.D., P.Eng.,
• Robert X. Gao Ph.D.
• …show all 2hide
  

ISBN: 978-1-84628-268-3 (Print) 978-1-84628-269-0  (Online)

About this book
Manufacturing systems and processes are becoming increasingly complex, making more rational decision-making in process control a necessity. Better information gathering and analysis techniques are needed and condition monitoring is gaining attention from researchers worldwide as a framework that will enable these improvements.
Condition Monitoring and Control for Intelligent Manufacturing brings together the world’s authorities on condition monitoring to provide a broad treatment of the subject accessible to researchers and practitioners in manufacturing industry.
The book presents a wide and comprehensive review of the key areas of research in machine condition monitoring and control, before focusing on an in-depth treatment of each important technique, from multi-domain signal processing for defect diagnosis to web-based information delivery for real-time control.
Condition Monitoring and Control for Intelligent Manufacturing is a valuable resource for researchers in manufacturing and control engineering, as well as practising engineers in industries from automotive to packaging manufacturing.

The Springer Series in Advanced Manufacturing publishes the best teaching and reference material to support students, educators and practitioners in manufacturing technology and management. This international series includes advanced textbooks, research monographs, edited works and conference proceedings covering all subjects in advanced manufacturing. The series focuses on new topics of interest, new treatments of more traditional areas and coverage of the applications of information and communication technology (ICT) in manufacturing.

Table of contents Monitoring and Control of Machining
Precision Manfacturing Process Monitoring with Acoustic Emission
Tool Condition Monitoring in Machining
Monitoring System for Grinding Processes
Condition Monitoring of Rotary Machines
Advanced Diagnostic and Prognostic Techniques for Rolling Element Bearings
Sensor Placement and Signal Processing for Bearing Condition Monitoring
Monitoring and Diagnosis of Sheet Metal Stamping Processes
Robust State Indicators of Gearboxes Using Adaptive Parametric Modeling
Signal Processing in Manufacturing Monitoring
Autonomous Active-Sensor Networks for High-Accuracy Monitoring in Manfacturing
Remote Monitoring and Control in Distributed Manufacturing Environment
An Intelligent Nanofabrication Probe with Function of Surface Displacement/Profile Measurement
Smart Transducer Interface Standards for Condition Monitoring and Control of Machines
Rocket Testing and Integrated System Health Management

Lihui Wang is a professor of virtual manufacturing at the University of Skövde’s Virtual Systems Research Centre in Sweden. He was previously a senior research scientist at the Integrated Manufacturing Technologies Institute, National Research Council of Canada. He is also an adjunct professor in the Department of Mechanical and Materials Engineering at the University of Western Ontario, and a registered professional engineer in Canada. His research interests and responsibilities are in web-based and sensor-driven real-time monitoring and control, distributed machining process planning, adaptive assembly planning, collaborative design, supply chain management, as well as intelligent and adaptive manufacturing systems. Dr. Robert X. Gao is an Associate Professor of Mechanical Engineering at the University of Massachusetts Amherst, USA. He received his B.S. degree from China, and his M.S. and Ph.D. from the Technical University Berlin, Germany, in 1982, 1985, and 1991, respectively. Since starting his academic career in 1992, he has been conducting research in the general area of embedded sensors and sensor networks, "smart" electromechanical systems, wireless data communication, and signal processing for machine health monitoring, diagnosis, and prognosis. Dr. Gao has published over 100 refereed papers on journals and international conferences, and has one US patent and two pending patent applications on sensing. He is an Associate Editor for the IEEE Transactions on Instrumentation and Measurement, and served as the Guest Editor for the Special Issue on Sensors of the ASME Journal of Dynamic Systems, Measurement, and Control, published in June, 2004. Condition-based Monitoring and Control for Intelligent Manufacturing has arisen from the Flexible Automation and Intelligent Manufacturing (FAIM 2004) conference, held in Toronto, Canada on July12-14 2004. Thirty papers have been selected out of 170 presented at the conference and the authors of these papers have been invited to submit extended updated versions of these papers in order to create a state of the art review of condition-based monitoring and control in manufacturing.