Learning and Reasoning Techniques for Automatic Feature Recognition from CAD Models
نویسندگان
چکیده
During the product development, Automatic Feature Recognition (AFR) techniques are an important tool for achieving a true integration of design and manufacturing stages. In particular, AFR systems offer capabilities for the identification in Computer-Aided Design (CAD) models of high-level geometrical entities, features that are semantically significant for manufacturing operations. However, the recognition performances of most of the existing AFR systems are limited to the requirements of specific manufacturing applications. This paper presents a new AFR method that facilitates the deployment of such systems in different application domains. In particular, the method provides a formal reasoning mechanism that combines the advantages of inductive and deductive techniques for feature recognition from Boundary Representation (B-Rep) part models. The proposed AFR method is implemented within a prototype feature recognition system and its capabilities are verified on a benchmarking part.
منابع مشابه
Knowledge acquisition techniques for feature recognition in CAD models
Automatic Feature Recognition (AFR) techniques are an important tool for achieving a true integration of design and manufacturing stages during the product development. In particular, AFR systems offer capabilities for recognising high-level geometrical entities, features, in Computer-Aided Design (CAD) models. However, the recognition performances of most of the existing AFR systems are limite...
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