Extracting Alternative Machining Features: An Algorithmic Approach

Automated recognition of features from CAD models has been attempted for a wide range of application domains. In this paper we address the problem of representing and recognizing a complete class of features in alternative interpretations for a given design. We present a methodology for recognizing a class of machinable features and addressing the computational problems posed by the existence of feature-based alternatives. Our approach addresses a class of volumetric features that describe material removal volumes made by operations on 3-axis vertical machining centers including: drilling, pocket-milling, slot-milling, face-milling, chamfering, lleting, and blended surfaces. This approach recognizes intersecting features and is complete over all features in our class; i.e., for any given part, the algorithm produces a set containing all features in our class that correspond to possible operations for machining that part. This property is of particular significance in applications where consideration of di erent manufacturing alternatives is crucial. This approach employs a class of machinable features expressible as MRSEVs (a STEP-based library of machining features). An example of this methodology has been implemented using the ACIS solid modeler and the National Institutes of Health C++ class library. Current address: National Institute of Standards and Technology, Center for Manufacturing Engineering, Manufacturing Systems Integration Division, Building 220, Room A-127, Gaithersburg, MD 20899. Current address: Rapid Manufacturing Laboratory, The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213