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Condition Monitoring and Control for Intelligent Manufacturing

  • Book
  • © 2006

Overview

Editors:
  1. Lihui Wang

    1. Integrated Manufacturing Technologies Institute, National Research Council of Canada, London, Canada

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  2. Robert X. Gao

    1. Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, USA

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    You can also search for this editor in PubMed   Google Scholar

  • Only book to cover state of the art research into intelligent condition monitoring, an important area of manufacturing engineering research

Part of the book series: Springer Series in Advanced Manufacturing (SSAM)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xix
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  2. Monitoring and Control of Machining

    • A. Galip Ulsoy
    Pages 1-32

  3. Precision Manufacturing Process Monitoring with Acoustic Emission

    • D. E. Lee, Inkil Hwang, C. M. O. Valente, J. F. G. Oliveira, David A. Dornfeld
    Pages 33-54

  4. Tool Condition Monitoring in Machining

    • Mo A. Elbestawi, Mihaela Dumitrescu, Eu-Gene Ng
    Pages 55-82

  5. Monitoring Systems for Grinding Processes

    • Bernhard Karpuschewski, Ichiro Inasaki
    Pages 83-107

  6. Condition Monitoring of Rotary Machines

    • N. Tandon, A. Parey
    Pages 109-136

  7. Advanced Diagnostic and Prognostic Techniques for Rolling Element Bearings

    • Thomas R. Kurfess, Scott Billington, Steven Y. Liang
    Pages 137-165

  8. Sensor Placement and Signal Processing for Bearing Condition Monitoring

    • Robert X. Gao, Ruqiang Yan, Shuangwen Sheng, Li Zhang
    Pages 167-191

  9. Monitoring and Diagnosis of Sheet Metal Stamping Processes

    • R. Du
    Pages 193-218

  10. Robust State Indicators of Gearboxes Using Adaptive Parametric Modeling

    • Yimin Zhan, Viliam Makis
    Pages 219-244

  11. Signal Processing in Manufacturing Monitoring

    • C. James Li
    Pages 245-265

  12. Autonomous Active-sensor Networks for High-accuracy Monitoring in Manufacturing

    • Ardevan Bakhtari, Beno Benhabib
    Pages 267-288

  13. Remote Monitoring and Control in a Distributed Manufacturing Environment

    • Lihui Wang, Weiming Shen, Peter Orban, Sherman Lang
    Pages 289-313

  14. An Intelligent Nanofabrication Probe for Surface Displacement/Profile Measurement

    • Wei Gao
    Pages 315-346

  15. Smart Transducer Interface Standards for Condition Monitoring and Control of Machines

    • Kang B. Lee
    Pages 347-372

  16. Rocket Testing and Integrated System Health Management

    • Fernando Figueroa, John Schmalzel
    Pages 373-391

  17. Back Matter

    Pages 393-399
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Keywords

About this book

Manufacturing systems and processes are becoming more complex, so more rational decision-making in process control is a necessity. Better information gathering and analysis techniques are needed and condition  monitoring is seen 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 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.

Researchers in manufacturing and control engineering, as well as practising engineers in industries from automotive to packaging manufacturing will find this book valuable.

Editors and Affiliations

  • Integrated Manufacturing Technologies Institute, National Research Council of Canada, London, Canada

    Lihui Wang

  • Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, USA

    Robert X. Gao

About the editors

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 havebeen 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.

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