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Optimal design of a flexible transferring system in press automation using fuzzy clustering

Hossein Rouhani (Irankhodro Company (IKCO), Tehran, Iran and Applied Design Center of Excellence, Mechanical Engineering Department, University of Tehran, Tehran, Iran)
Alireza Fazlirad (Irankhodro Company (IKCO), Tehran, Iran and Applied Design Center of Excellence, Mechanical Engineering Department, University of Tehran, Tehran, Iran)
Babak N. Araabi (Control and Intelligent Processing Center of Excellence, Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran)
Caro Lucas (Control and Intelligent Processing Center of Excellence, Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran)

Assembly Automation

ISSN: 0144-5154

Article publication date: 1 March 2005

826

Abstract

Purpose

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Modern day manufacturing has seen the replacement of manual transfer of parts between press machines with automatic transfer systems. Higher automation productivity demands greater flexibility of transfer devices. This paper deals with methods to improve the flexibility of fixtures designed to transfer parts between press machines.

Design/methodology/approach

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Describes methods to improve the flexibility of fixtures designed to transfer parts between press machines in Press Shop 3 at Iran Khodro Company (IKCO). A fuzzy C means clustering‐based method is developed to optimize the number and arrangement of actuators for each fixture. Economical aspects of this novel design are addressed as well.

Findings

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The simulation results suggest that application of a flexible fixtures system and use of linear motors was the best method of adding flexibility to the loader‐unloader system.

Originality/value

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Provides evidence that flexible components are indispensable to increasing production speed and reliability in an automated system.

Keywords

Citation

Rouhani, H., Fazlirad, A., Araabi, B.N. and Lucas, C. (2005), "Optimal design of a flexible transferring system in press automation using fuzzy clustering", Assembly Automation, Vol. 25 No. 1, pp. 53-58. https://doi.org/10.1108/01445150510579003

Publisher

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Emerald Group Publishing Limited

Copyright © 2005, Emerald Group Publishing Limited

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