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Auto panel die quotation system based on back propagation neural network

  • Wei Lin
  • , Yu Ming Zhu
  • , Ji Hong Liu*
  • *Corresponding author for this work
  • Beihang University

Research output: Contribution to journalArticlepeer-review

Abstract

It was difficult for traditional die quotation methods to satisfy high precision and efficiency requirements in modern markets. To deal with this problem, a panel die quotation method based on Back Propagation Neural Network (BPNN) was proposed. Firstly, an auto panel die quotation method architecture including BPNN, weight method and man-hour method was proposed, which could support the whole process quotation. Then, the auto panel die quotation system supporting industry chain collaboration was developed, and integrated with the public service platform of auto die industry chain collaboration. Different quotation phases and the various application objects in different industry chains could be supported by the system. Finally, examples were used to verify the applicability, rationality and effectiveness of the BPNN quotation method.

Original languageEnglish
Pages (from-to)2280-2287
Number of pages8
JournalJisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS
Volume15
Issue number11
StatePublished - Nov 2009

Keywords

  • Back propagation neural network
  • Die quotation
  • Industry chain collaboration
  • Panel

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