An Aircraft Structural Component Process Route Recommendation Engine Based on ANN-LCS Algorithm

Linhao Qin, Dewei Fu, Zhenjun Ming*, Hongpeng Zhang, Hu Lu, Qiang Li, Baoguo Chen, Qin Wen, Mengmin Xu, Ruiqiang Lyu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A process route recommendation engine for aviation structural components based on ANN-LCS algorithm is introduced. By processing the machining process knowledge of aviation structural components, defining their basic information and process route data, and then constructing and training an ANN (Artificial Neural Network) to classify parts. Based on part classification, the LCS (Longest Common Substring) algorithm based on dynamic programming is used to generate process routes. Through the testing of process route recommendation examples, the results show that this method can effectively obtain and select feasible process routes in the process design stage.

Original languageEnglish
Title of host publication2024 7th International Conference on Computer Information Science and Application Technology, CISAT 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages796-802
Number of pages7
ISBN (Electronic)9798350375107
DOIs
Publication statusPublished - 2024
Event7th International Conference on Computer Information Science and Application Technology, CISAT 2024 - Hangzhou, China
Duration: 12 Jul 202414 Jul 2024

Publication series

Name2024 7th International Conference on Computer Information Science and Application Technology, CISAT 2024

Conference

Conference7th International Conference on Computer Information Science and Application Technology, CISAT 2024
Country/TerritoryChina
CityHangzhou
Period12/07/2414/07/24

Keywords

  • artificial neural network
  • dynamic programming
  • longest common sequence
  • process route recommendation

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