Multi-view feature modeling for design-for-additive manufacturing. (January 2019)
- Record Type:
- Journal Article
- Title:
- Multi-view feature modeling for design-for-additive manufacturing. (January 2019)
- Main Title:
- Multi-view feature modeling for design-for-additive manufacturing
- Authors:
- Li, Lei
Liu, Jikai
Ma, Yongsheng
Ahmad, Rafiq
Qureshi, Ahmed - Abstract:
- Abstract: This paper presents a design-for-additive manufacturing (DfAM) methodology based on multi-view feature modeling. Multi-view feature model is a unified information carrier which contains the data of a product related to different lifecycle stages. The information can be selectively extracted, interpreted and clustered to provide a specific view of the product and thus to facilitate the design-for-X, e.g. manufacturability design with the manufacturing view and mechanical property enhancement with the analysis view. Feature conversion provides a mechanism to translate the lifecycle stage-related descriptions of the product, which therefore reveals the underlying dependencies and addresses the complexities in associative modeling. For instance, manufacturing information has to be extracted to support the construction of the analysis model, because process planning of additive manufacturing (AM) has a direct impact on the material properties. The main benefit of multi-view feature modeling for AM is that integrated product development can be realized to simultaneously take several engineering aspects into account, e.g. concurrent design of the structural mechanical properties and manufacturability. Apparently, performing the integrated design can enhance the overall design quality and significantly improve the product development efficiency. Specifically in this paper, the design, manufacturing, and analysis views of an AM product will be modeled. Level set will beAbstract: This paper presents a design-for-additive manufacturing (DfAM) methodology based on multi-view feature modeling. Multi-view feature model is a unified information carrier which contains the data of a product related to different lifecycle stages. The information can be selectively extracted, interpreted and clustered to provide a specific view of the product and thus to facilitate the design-for-X, e.g. manufacturability design with the manufacturing view and mechanical property enhancement with the analysis view. Feature conversion provides a mechanism to translate the lifecycle stage-related descriptions of the product, which therefore reveals the underlying dependencies and addresses the complexities in associative modeling. For instance, manufacturing information has to be extracted to support the construction of the analysis model, because process planning of additive manufacturing (AM) has a direct impact on the material properties. The main benefit of multi-view feature modeling for AM is that integrated product development can be realized to simultaneously take several engineering aspects into account, e.g. concurrent design of the structural mechanical properties and manufacturability. Apparently, performing the integrated design can enhance the overall design quality and significantly improve the product development efficiency. Specifically in this paper, the design, manufacturing, and analysis views of an AM product will be modeled. Level set will be adopted as the basic mathematical tool for multi-view feature modeling because of its compatibility with all the concerned design activities. The effectiveness of the integrated product design will be demonstrated by numerical case studies. … (more)
- Is Part Of:
- Advanced engineering informatics. Volume 39(2019)
- Journal:
- Advanced engineering informatics
- Issue:
- Volume 39(2019)
- Issue Display:
- Volume 39, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 39
- Issue:
- 2019
- Issue Sort Value:
- 2019-0039-2019-0000
- Page Start:
- 144
- Page End:
- 156
- Publication Date:
- 2019-01
- Subjects:
- Multi-view feature modeling -- Level set -- Design-for-additive manufacturing -- Integrated product development
Computer-aided engineering -- Periodicals
Engineering -- Data processing -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14740346 ↗
http://books.google.com/books?id=KhFVAAAAMAAJ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.aei.2018.12.004 ↗
- Languages:
- English
- ISSNs:
- 1474-0346
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.851100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 9585.xml