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A dynamically updatable knowledge graph construction method for computer-aided process planning and design.

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Title: A dynamically updatable knowledge graph construction method for computer-aided process planning and design.
Authors: Zhang, En1 (AUTHOR), Zhang, Sheng-Wen1 (AUTHOR) 221210201323@stu.just.edu.cn, Jia, Jia-Le1 (AUTHOR)
Source: Journal of Engineering Design. Jul-Sep2025, Vol. 36 Issue 7-9, p1551-1584. 34p.
Subjects: Computer-aided process planning, Knowledge graphs, Production planning, Process optimization, Knowledge base, Knowledge management
Abstract: The process knowledge base serves as a fundamental component in the intelligent design of Computer-Aided Process Planning (CAPP), as it determines system intelligence and influences design quality. Within the realm of designing complex products, a significant volume of valuable process knowledge is generated. However, effectively managing this knowledge presents challenges, leading to poor accessibility for subsequent use and significant data loss. The existing process knowledge graphs lacks an efficient, and dynamic update mechanism, which cannot meet the changing production requirements of current enterprises. Therefore, a dynamically updatable knowledge graph construction method for CAPP is proposed in this work. Firstly, a knowledge representation model that combines product design processes and manufacturing data is proposed. Secondly, a Process Knowledge Learning Forgetting Model is proposed for dynamically updating the process knowledge graph. Finally, a prototype system is developed, and experimental analysis is conducted. Comparative evaluations against alternative to other methods, demonstrate that the proposed method enhances work efficiency and design accuracy in CAPP by 10% and 2% respectively. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Engineering Design is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A dynamically updatable knowledge graph construction method for computer-aided process planning and design.
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  Data: <searchLink fieldCode="AR" term="%22Zhang%2C+En%22">Zhang, En</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Sheng-Wen%22">Zhang, Sheng-Wen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 221210201323@stu.just.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Jia%2C+Jia-Le%22">Jia, Jia-Le</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Engineering+Design%22">Journal of Engineering Design</searchLink>. Jul-Sep2025, Vol. 36 Issue 7-9, p1551-1584. 34p.
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  Data: <searchLink fieldCode="DE" term="%22Computer-aided+process+planning%22">Computer-aided process planning</searchLink><br /><searchLink fieldCode="DE" term="%22Knowledge+graphs%22">Knowledge graphs</searchLink><br /><searchLink fieldCode="DE" term="%22Production+planning%22">Production planning</searchLink><br /><searchLink fieldCode="DE" term="%22Process+optimization%22">Process optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Knowledge+base%22">Knowledge base</searchLink><br /><searchLink fieldCode="DE" term="%22Knowledge+management%22">Knowledge management</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The process knowledge base serves as a fundamental component in the intelligent design of Computer-Aided Process Planning (CAPP), as it determines system intelligence and influences design quality. Within the realm of designing complex products, a significant volume of valuable process knowledge is generated. However, effectively managing this knowledge presents challenges, leading to poor accessibility for subsequent use and significant data loss. The existing process knowledge graphs lacks an efficient, and dynamic update mechanism, which cannot meet the changing production requirements of current enterprises. Therefore, a dynamically updatable knowledge graph construction method for CAPP is proposed in this work. Firstly, a knowledge representation model that combines product design processes and manufacturing data is proposed. Secondly, a Process Knowledge Learning Forgetting Model is proposed for dynamically updating the process knowledge graph. Finally, a prototype system is developed, and experimental analysis is conducted. Comparative evaluations against alternative to other methods, demonstrate that the proposed method enhances work efficiency and design accuracy in CAPP by 10% and 2% respectively. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Engineering Design is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/09544828.2025.2450762
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      – Code: eng
        Text: English
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        PageCount: 34
        StartPage: 1551
    Subjects:
      – SubjectFull: Computer-aided process planning
        Type: general
      – SubjectFull: Knowledge graphs
        Type: general
      – SubjectFull: Production planning
        Type: general
      – SubjectFull: Process optimization
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      – SubjectFull: Knowledge base
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      – SubjectFull: Knowledge management
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          Dates:
            – D: 01
              M: 07
              Text: Jul-Sep2025
              Type: published
              Y: 2025
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