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  • Conference proceedings
  • © 2018

Advanced Manufacturing and Automation VII

Editors:

  • Gathers selected presentations from the 7th International Workshop of Advanced Manufacturing and Automation (IWAMA 2017), Changshu, China
  • Presents latest research findings from leading academic researchers and engineers from industry
  • Benefits engineers facing challenges to keep on top of the emerging trends through continuous research and development

Part of the book series: Lecture Notes in Electrical Engineering (LNEE, volume 451)

Conference series link(s): IWAMA: International Workshop of Advanced Manufacturing and Automation

Conference proceedings info: IWAMA 2017.

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Table of contents (66 papers)

  1. Introduction of Cyber-Physical System in Robotized Press-Brake Line for Metal Industry

    • Beibei Shu, Gabor Sziebig, Bjørn Solvang
    Pages 181-186
  2. Dynamic Balance System Design and Control for High-Branch Pruning Machine

    • Yang Li, Shuai Du, Xinxue Zhao, Ziru Niu, Jin Yuan
    Pages 187-196
  3. Braking Distance Monitoring System for Escalator

    • Xiaomei/XM Jiang, Shuguang/SG Niu, Lanzhong/LZ Guo
    Pages 197-205
  4. Design of Large Tonnage Elevator Sheave Block

    • Lanzhong Guo, Xiaomei Jiang, Yannian Rui
    Pages 207-217
  5. Strategic Framework for Manual Assembly System Design

    • Logan Reed Vallandingham, Jo Wessel Strandhagen, Erlend Alfnes, Jan Ola Strandhagen
    Pages 229-237
  6. Ultrasonic Sensing System Design and Accurate Target Identification for Targeted Spraying

    • Xinxue Zhao, Yang Li, Xuemei Liu, Ziru Niu, Jin Yuan
    Pages 245-253
  7. Review of Technology for Strengthening Effect of Fe Element in Al Alloys

    • De-Qin Sun, Zi-Qiang Zhou, Su Zhu, Pei-Jun Wu
    Pages 265-273
  8. Human Centered Automation System for ELV Disassembly Line

    • Guohong Dai, Ziqiang Zhou
    Pages 347-355
  9. Rolling Bearing Fault Diagnosis Using Deep Learning Network

    • Shenghao Tang, Yuqiu Yuan, Li Lu, Shuang Li, Changqing Shen, Zhongkui Zhu
    Pages 357-365
  10. An Automatic Feature Learning and Fault Diagnosis Method Based on Stacked Sparse Autoencoder

    • Yumei Qi, Changqing Shen, Jie Liu, Xuwei Li, Dading Li, Zhongkui Zhu
    Pages 367-375

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  1. Advanced Manufacturing and Automation VII

About this book

The proceedings brings together a selection of papers from the 7th International Workshop of Advanced Manufacturing and Automation (IWAMA 2017), held in Changshu Institute of Technology, Changshu, China on September 11–12, 2017. Most of the topics are focusing on novel techniques for manufacturing and automation in Industry 4.0. These contributions are vital for maintaining and improving economic development and quality of life. The proceeding will assist academic researchers and industrial engineers to implement the concepts and theories of Industry 4.0 in industrial practice, in order to effectively respond to the challenges posed by the 4th industrial revolution and smart factories.

Editors and Affiliations

  • Department of Production and Quality Engineering, Norwegian University of Science and Technology, Trondheim, Norway

    Kesheng Wang

  • School of Business, Plymouth University, Plymouth, United Kingdom

    Yi Wang

  • Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim, Norway

    Jan Ola Strandhagen

  • Shanghai Second Polytechnic University, Shanghai, China

    Tao Yu

About the editors

Professor Kesheng Wang has been a Professor and director of the Knowledge Discovery Laboratory at the Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology (NTNU), Norway. He became an elected member of the Norwegian Academy of Technological Sciences in 2006. Prof. Wang has published 22 books, 10 book chapters and over 270 technical peer-reviewed papers in international journals and conferences. He also has extensive experience with coordinating cooperation projects with many industrial companies and national, international and EU projects. Professor Wang’s current areas of interest are intelligent manufacturing systems, data mining and knowledge discovery, radio-frequency identification (RFID), predictive maintenance and Industry 4.0/Logistics 4.0.

Dr. Yi Wang obtained his PhD from the Manufacturing Engineering Center, Cardiff University, UK in 2008. He is currently a Lecturer at the School of Business and Management, Plymouth University, UK. He holds various visiting professorships in several universities worldwide. Dr. Wang’s research interests include supply chain management, logistics, operation management, culture management, information systems, game theory, data analysis, semantics and ontology analysis, and neuromarketing. He has published 35 technical peer-reviewed papers in international journals and conferences. He has co-authored two monographs: Operations Management for Business in 2008 and Data Mining for Zero-defect Manufacturing in 2012.

Professor Jan Ola Strandhagen is a Professor at the Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology (NTNU), Norway. He was previously director of the research center SFI Norman in SINTEF. He holds a PhD in Production Engineering from NTNU (1994). His research has focused on production management and control, logistics, manufacturing economics and strategies. He has managed and executed R&D projects in close collaboration with a wide variety of Norwegian companies and participated as researcher and project manager in several European projects.

Professor Tao Yu is the President of Shanghai Polytechnic University, Shanghai, China and Professor at Shanghai University. He is a committee member of the International Federation for Information Processing (IFIP)/TC5. Prof. Yu has published more than one hundred academic papers. His research interests include mechatronics, computer integrated manufacturing systems and grid manufacturing.

Bibliographic Information

Buy it now

Buying options

eBook USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 379.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access