INTEGRATION OF FEATURE-BASED DESIGN AND FEATURE RECOGNITION

Process planning for machined parts typically requires that a part be described through machining features such as holes, slots and pockets. This paper presents a novel feature finder, which automatically gener ates a part interpretation in terms of machining features, by utilizin g information from a variety of sources such as nominal geometry, tole rances and attributes, and design features. The feature finder strives to produce a desirable interpretation of the part as quickly as possi ble. If this interpretation is judged unacceptable by a process planne r, alternatives can be generated on demand. The feature finder uses a hint-based approach, and combines artificial intelligence techniques, such as blackboard architecture and uncertain reasoning, with the geom etric completion procedures first introduced in the OOFF system previo usly developed at USC. (C) 1997 Elsevier Science Ltd.