DocumentCode :
3512496
Title :
Developing a rule engine for Automated Feature Recognition from CAD models
Author :
Zhang, Hao Lan ; Van der Velden, Christian ; Yu, Xinghuo ; Bil, Cees ; Jones, Tim ; Fieldhouse, Ian
Author_Institution :
Sch. of Comput. & Electr. Eng., RMIT Univ., Melbourne, VIC, Australia
fYear :
2009
fDate :
3-5 Nov. 2009
Firstpage :
3925
Lastpage :
3930
Abstract :
The detailed development phase in modern engineering project lifecycles is characterised by the iterative use of a number of engineering software tools. Inefficient integration between these tools often results in a high volume of manual data manipulation, for example the derivation of analysis and manufacturing models from detailed design models. The automatic recognition of engineering features from product geometry has potential to improve integration efficiency and reduce time and costs of downstream processes of Computer Aided Design (CAD) system based design. This paper introduces a methodology for developing and executing rules to identify engineering features from geometric data. The methodology has been implemented in an Automated Feature Recognition (AFR) system that identifies and extracts analysis features to feed stress analysis algorithms.
Keywords :
CAD; feature extraction; knowledge based systems; production engineering computing; AFR system; CAD models; automated feature recognition; computer aided design; engineering features; engineering software tools; product geometry; rule engine; stress analysis algorithms; Algorithm design and analysis; Computational geometry; Costs; Data engineering; Data mining; Design automation; Design engineering; Engines; Software tools; Virtual manufacturing; AFR; Aerospace Component Design; CAD; Feature Recognition; Rule-based Systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, 2009. IECON '09. 35th Annual Conference of IEEE
Conference_Location :
Porto
ISSN :
1553-572X
Print_ISBN :
978-1-4244-4648-3
Electronic_ISBN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2009.5415343
Filename :
5415343
Link To Document :
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