© 2007

Process Planning and Scheduling for Distributed Manufacturing

  • Lihui Wang
  • Weiming Shen

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

Table of contents

  1. Front Matter
    Pages i-xix
  2. V. Y. M. Tsang, B. K. K. Ngai, G. Q. Huang, V. H. Y. Lo, K. C. Cheng
    Pages 31-59
  3. Dusan N. Sormaz, Jaikumar Arumugam, Chandrasekhar Ganduri
    Pages 61-90
  4. Paul Dean, Yiliu Tu, Deyi Xue
    Pages 109-136
  5. Yiming Kevin Rong
    Pages 137-166
  6. Paulo Sousa, Carlos Ramos, José Neves
    Pages 167-190
  7. Scott S. Walker, Douglas H. Norrie, Robert W. Brennan
    Pages 213-241
  8. Sev Nagalingam, Grier Lin, Dongsheng Wang
    Pages 269-294
  9. Weidong Li, S. K. Ong, A. Y. C. Nee
    Pages 295-309
  10. Nobuhiro Sugimura, Rajesh Shrestha, Yoshitaka Tanimizu, Koji Iwamura
    Pages 311-334
  11. Nazrul I. Shaikh, Michael Masin, Richard A. Wysk
    Pages 365-392
  12. Back Matter
    Pages 423-429

About this book


The process planning and scheduling issues of intelligent and distributed manufacturing are crucial nowadays due to the need for enterprises to be adaptive, re-configurable, collaborative and flexible enough to support the emergence of worldwide competition and dynamic and mass-customised markets. With this increasing dynamism of decentralised manufacturing systems and processes, more effective and efficient decision-making techniques are needed.

Process Planning and Scheduling for Distributed Manufacturing focuses on emerging technologies for distributed intelligent decision-making in process planning and dynamic scheduling. As a collection of chapters on state-of-the-art researches in this area, this book presents a review of several key research areas in process planning and scheduling (e.g., adaptive process planning, dynamic scheduling, and process planning and scheduling integration), and provides an in-depth treatment of particular techniques, from function block enabled process planning to agent-based resource scheduling. Each chapter addresses a specific problem domain and offers practical solutions to solve the problem.

Given the essential role manufacturing plays in the economic development of all industrial nations, Process Planning and Scheduling for Distributed Manufacturing will be of interest to academic researchers, practising engineers and graduate students for whom it will provide a better understanding of the present state and future trends of research in this important area.


Manufacturing Manufacturing System Trend artificial intelligence computer-aided design (CAD) computer-integrated manufacturing (CIM) control data mining design machining maintenance modeling optimal control production scheduling

Editors and affiliations

  • Lihui Wang
    • 1
  • Weiming Shen
    • 1
  1. 1.Integrated Manufacturing Technologies InstituteNational Research Council of CanadaLondonCanada

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 Weiming Shen is an Senior Research Officer in the Integrated Manufacturing Technologies Institute, National Research Council of Canada. He is also an Adjunct Full Professor of Systems Design Engineering at the University of Waterloo. His research interests are in Agents and Multi-Agent Systems, Concurrent Engineering, Collaborative Design and Manufacturing, Virtual Design and Manufacturing, Virtual Enterprises and Supply Chain Management, e-Commerce / e-Businesses, and Knowledge-Based Systems.

Bibliographic information

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