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An approach to automatic adaptation of assembly models
- Source :
- Computers in Industry. 75:67-79
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- A novel approach to effectively enable the assembly model adaptation automatic, independent of domain knowledge library and low demand on shape similarity. This is achieved by dividing the adaptation into two steps:First, automatic kinematic semantics adaptation is achieved by using a heuristic processing method on the attributed kinematic graphs instead of knowledge library supporting.Then, mainly guided by the result of automatic kinematic semantics adaptation, automatic geometry adaptation is performed to make the geometry adaptation low demand on shape similarity.A new method to automatically and precisely identify the high-level geometry correspondences between two non-registered assembly models based on their attributed kinematic graphs and a heuristic graph matching method. Adaptation plays a fundamental role in case-based design. However, after decades of efforts, automatic adaptation is still an open issue. In works of case-based design, a designer usually chooses a start-up product model (a candidate model) of moderate complexity based on a query model possessing primary new design requirements (kinematic semantics and geometry), then achieves the target design by adapting the candidate model according to the new design requirements and human interventions are often indispensable. To smartly adapt the candidate model to fit the new design requirements, a novel approach to automatic adaptation of assembly models is proposed in this paper. First, in order to effectively identify the corresponding links and interfaces between two non-preregistered assembly models as relevant elements, an attributed kinematic graph is put forward and adopted. Second, based on the attributed kinematic graph, the kinematic semantics of the candidate model is automatically adapted to that of the query model. Third, through performing interface layout transferring, the geometry of the candidate model is automatically adapted to that of the query model based on the corresponding links and interfaces. A prototype system is also implemented to verify the effectiveness of the proposed approach.
- Subjects :
- 0209 industrial biotechnology
Theoretical computer science
General Computer Science
Computer science
business.industry
General Engineering
020207 software engineering
02 engineering and technology
Kinematics
Machine learning
computer.software_genre
Graph
Low demand
Processing methods
020901 industrial engineering & automation
0202 electrical engineering, electronic engineering, information engineering
Domain knowledge
Product model
Artificial intelligence
business
computer
Subjects
Details
- ISSN :
- 01663615
- Volume :
- 75
- Database :
- OpenAIRE
- Journal :
- Computers in Industry
- Accession number :
- edsair.doi...........4cb4bed2f33d6f46991668a88bc47cac
- Full Text :
- https://doi.org/10.1016/j.compind.2015.06.005