Knowledge representation and push of machining process driven by geometric variation

Chunlei Li, Rong Mo, Zhiyong Chang, Haicheng Yang, Dongliang Zhang, Ying Xiang

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

To deal with the difficult problem of knowledge representation and push in machining process, a basic view that the geometry variation process of machining feature was the direct carrier of process knowledge was proposed. The knowledge representation of machining process driven by geometric variation and process knowledge push model based on knowledge representation were presented. The geometric variation of parts machining process was represented, and a new process knowledge model that could describe the formation of machining feature was established. The knowledge network model was built by applying complex network theory, and the knowledge push process was defined, which realized the accurate knowledge push based on process design task. Experimental results showed that the proposed method was feasible and effective.

Original languageEnglish
Pages (from-to)1434-1446
Number of pages13
JournalJisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS
Volume22
Issue number6
DOIs
StatePublished - 1 Jun 2016

Keywords

  • Complex network
  • Geometric variation
  • Machining feature
  • Process knowledge push
  • Process knowledge representation

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