Using an aritificial neural network to assist roll design in cold roll-forming processes

AW Downes, Peter Hartley

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Cold roll-forming is a highly efficient and economical method for the production of sheet metal products, compared to rival processes. It has a major difficulty, however, because it frequently experiences quality problems such as longitudinal curvature. The tool design method is largely subjective and often involves a trial and error procedure where rolls are tested in the workshop. This paper develops a technique using an artificial neural network to assist in the design of roll-forming tools. (c) 2006 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)319-322
Number of pages4
JournalJournal of Materials Processing Technology
Volume177
DOIs
Publication statusPublished - 3 Jul 2006

Keywords

  • radial basis functions
  • artificial neural networks
  • integral shapes
  • cold roll-forming
  • longitudinal curvature
  • springback

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