A control framework to support responsive manufacturing

A control framework to support responsive manufacturing This paper is concerned with reducing the barriers imposed on the flexibility and responsiveness of automated manufacturing systems by current control software technology. The general question that is addressed by this research is, how can insights be gained from the manufacturing system that can assist the control system in meeting this goal of responsive behavior? The approach that is taken is to investigate appropriate means of integrating available manufacturing system information into the control system. A framework for integrating status information to control an automated assembly line is introduced that combines both transient information (e.g. station queue length) and steady‐state information (e.g. station gradient estimates) obtained by observing the operation of the assembly line. It is shown that, through the use of an appropriately designed fuzzy‐logic controller (FLC), the combined information results in flow time performance superior to that achieved using the transient or steady‐state measures individually. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Agile Management Systems Emerald Publishing

A control framework to support responsive manufacturing

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Publisher
Emerald Publishing
Copyright
Copyright © 1999 MCB UP Ltd. All rights reserved.
ISSN
1465-4652
DOI
10.1108/14654659910296535
Publisher site
See Article on Publisher Site

Abstract

This paper is concerned with reducing the barriers imposed on the flexibility and responsiveness of automated manufacturing systems by current control software technology. The general question that is addressed by this research is, how can insights be gained from the manufacturing system that can assist the control system in meeting this goal of responsive behavior? The approach that is taken is to investigate appropriate means of integrating available manufacturing system information into the control system. A framework for integrating status information to control an automated assembly line is introduced that combines both transient information (e.g. station queue length) and steady‐state information (e.g. station gradient estimates) obtained by observing the operation of the assembly line. It is shown that, through the use of an appropriately designed fuzzy‐logic controller (FLC), the combined information results in flow time performance superior to that achieved using the transient or steady‐state measures individually.

Journal

International Journal of Agile Management SystemsEmerald Publishing

Published: Dec 1, 1999

Keywords: Flexible manufacturing systems; Computer‐integrated manufacturing; Modelling; Simulation

References

  • A fuzzy decision‐making system used to assign service priority for an automatic assembly station
    Foroughi, B.; Brennan, R.W.
  • Single run optimization of a SIMAN model for closed loop flexible assembly systems
    Suri, R.; Leung, Y.T.
  • A Course in Fuzzy Systems and Control
    Wang, L.

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