Belief representation of design mental model based on Design Rationale

Chen Ying, Jing Shikai*, Wang Yedong, Cheng Dada

*Corresponding author for this work

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

Abstract

Ignoring the designers' belief in the collaborative design process will lead to imperfect characterization of design information, and affect information sharing of collaborative designs, thus make the design inefficient. In order to solve this problem, this paper presents a belief representation method of designing a mental model based on Design Rationale. First, through the logic narration of designers, on the basis of the DR model, the knowledge semantic network is constructed based on the Bayesian Network. Then, the causality in the Bayesian Network is obtained by means of node conversion. Finally, the belief in designing mental models is calculated by reusing the design rationality for parameter learning. An example of cantilever beam structure design is used to verify the accuracy and effectiveness of the proposed method.

Original languageEnglish
Title of host publication2018 5th International Conference on Industrial Engineering and Applications, ICIEA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages510-514
Number of pages5
ISBN (Electronic)9781538657478
DOIs
Publication statusPublished - 15 Jun 2018
Event5th International Conference on Industrial Engineering and Applications, ICIEA 2018 - Singapore, Singapore
Duration: 26 Apr 201828 Apr 2018

Publication series

Name2018 5th International Conference on Industrial Engineering and Applications, ICIEA 2018

Conference

Conference5th International Conference on Industrial Engineering and Applications, ICIEA 2018
Country/TerritorySingapore
CitySingapore
Period26/04/1828/04/18

Keywords

  • Bayesian Network
  • Design Ration
  • belief representation
  • design mental model

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