Conventional CAD models only provide pure geometry and topology for mechanical designs such as vertices, edges, faces, simple primitives, and the relationship among them. Feature recognition is then required to interpret this low-level part information into high-level and domain-specific features such as machining features. Over the years, CAD has been undergoing fundamental changes toward the direction of feature-based design or design by features. Commercial implementations of FBD technique became available in the late 1980’s. One of the main benefits of adopting feature- based approach is the fact that features can convey and encapsulate designers’ intents in a natural way. In other words, the initial design can be synthesized quickly from the high-level entities and their relations, which a conventional CAD modeller is incapable of doing. However, such a feature-based design system, though capable of generating feature models as its end result, lacks the necessary link to a CAPP system, simply because the design features do not always carry the manufacturing information which is essential for process planning activities. This type of domain-dependent nature has been elaborated on in the previous chapter. In essence, feature recognition has become the first task of a CAPP system. It serves as an automatic and intelligent interpreter to link CAD with CAM, regardless of the CAD output being a pure geometric model or a feature model from a FBD system. To be specific, the goal of feature recognition systems is to bridge the gap between a CAD database and a CAPP system by automatically recognizing features of a part from the data stored in the CAD system, and based on the recognized features, to drive the CAPP system which produces process plans for manufacturing the part. Human interpretation of translating CAD data into technological information required by a CAPP system is thus minimized if not eliminated.
Automating Redesign of Sheet-Metal Parts in Automotive Industry Using KBE and CBR
