Technique for checking design rules for three-dimensional CAD data

Hariya, Masayuki; Nonaka, Norihiko; Shimizu, Yuki; Konishi, K.; Iwasaka, Takahiko

doi:10.1109/iccsit.2010.5565010

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…that do not belong to the designer background. Alternatively, several research studies propose a semantic approach (Hariya et al, 2010;García et al, 2020;Huang et al, 2015;Moitra and Palla, 2016). Given a CAD part, this approach translates the geometry and topology into an ontology that allows the detection of design errors by semantic reasoning.…”

Section: Cognitive Assistantsmentioning

confidence: 99%

“…Multi-dimensional concept of context in information retrieval (Skarka, 2007). (Ingwersen, 2007) Intelligent mobile applications, General context-awareness Person (Gu et al, 2004) Spatio-temporal (Tamine- Lechani et al, 2010;Hasanov et al, 2019;Kofod-Petersen and Aamodt, 2003) Location (Gu et al, 2004) Information on the user's position and movements (e.g. GPS information) (Gu et al, 2004) Social (Kofod-Petersen andAamodt, 2003) Organizational (Dhuieb et al, 2015), Collective (Ingwersen, 2007) Information on the social interactions among users (e.g.…”

Section: Stakeholdersmentioning

confidence: 99%

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CACDA: A knowledge graph for a context-aware cognitive design assistant

Huet

Pinquié

Véron

et al. 2021

Computers in Industry

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The design of complex engineered systems highly relies on a laborious zigzagging between computeraided design (CAD) software and design rules prescribed by design manuals. Despite the emergence of knowledge management techniques (ontology, expert system, text mining, etc.), companies continue to store design rules in large and unstructured documents. To facilitate the integration of design rules and CAD software, we propose a knowledge graph that structures a large set of design rules in a computable format. The knowledge graph organises entities of design rules (nodes), relationships among design rules (edges), as well as contextual information. The categorisation of entities and relationships in four subcontexts: semantic, social, engineering, and IT -facilitates the development of the data model, especially the definition of the "design context" concept. The knowledge graph paves the way to a context-aware cognitive design assistant. Indeed, connected to or embedded in a CAD software, a context-aware cognitive design assistant will capture the design context in near real time and run reasoning operations on the knowledge graph to extend traditional CAD capabilities, such as the recommendation of design rules, the verification of design solutions, or the automation of design routines. Our validation experiment shows that the current version of the context-aware cognitive design assistant is more efficient than the traditional document-based design. On average, participants using an unstructured design rules document have a precision of 0.36 whereas participants using our demonstrator obtain a 0.61 precision score. Finally, designers supported by the design assistant spend more time designing than searching for applicable design rules compared to the traditional design approach.

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Section: Cognitive Assistantsmentioning

confidence: 99%