Process Planning and Scheduling for Distributed Manufacturing / Edition 1

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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.

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Product Details

  • ISBN-13: 9781849966467
  • Publisher: Springer London
  • Publication date: 12/8/2010
  • Series: Springer Series in Advanced Manufacturing
  • Edition description: Softcover reprint of hardcover 1st ed. 2007
  • Edition number: 1
  • Pages: 429
  • Product dimensions: 9.21 (w) x 6.14 (h) x 0.91 (d)

Meet the Author

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.

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Table of Contents

An Effective Approach for Distributed Process Planning Enabled by Event-Driven Function Blocks
Web-based Polishing Process Planning Using Data Mining Techniques
Integration of Rule-based Process Selection with Virtual Machining for Distributed Manufacturing Planning
CyberCut: A Coordinated Pipeline of Design, Process Planning and Manufacture
Process Planning, Scheduling and Control for One-of-a-Kind Production
Setup Planning and Tolerance Analysis
Scheduling in Holonic Manufacturing Systems
Agent-based Dynamic Scheduling for Distributed Manufacturing
A Multi-agent System Implementation of an Evolutionary Approach to Production Scheduling
Distributed Scheduling in Multiple-factory Production with Machine Maintenance
Resource Scheduling for a Virtual CIM System
A Unified Model-based Integration of Process Planning and Scheduling
A Study on Integrated Process Planning and Scheduling System for Holonic Manufacturing
Managing Dynamic Demand Events in Semiconductor Manufacturing Chains by Optimal Control Modelling
A Parameter Perturbation Approach to Replanning Operations
STEP into Distributed Manufacturing with STEP-NC

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