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<p>Discusses an automatic feature recognizer that decomposes the total volume to be machined into volumetric features that satisfy stringent conditions for manufacturability, and correspond to operations typically performed in 3-axis machining centers. Unlike most of the previous research, the approach is based on general techniques for dealing with features with intersecting volumes. Feature interactions are represented explicitly in the recognizer's output, to facilitate spatial reasoning in subsequent planning stages. A generate-and-test strategy is used. OPS-5 production rules generate hints or clues for the existence of features, and post them on a blackboard. The clues are assessed, and those judged promising are processed to ensure that they correspond to actual features, and to gather information for process planning. Computational geometry techniques are used to produce the largest volumetric feature compatible with the available data. The feature's accessibility, and its interactions with others are analyzed. The validity tests ensure that the proposed features are accessible, do not intrude into the desired part, and satisfy other machinability conditions. The process continues until it produces a complete decomposition of the volume to be machined into fully-specified features.</p>
spatial reasoning; automatic feature recognition; machinable features; solid models; volumetric features; manufacturability; planning; generate-and-test strategy; OPS-5 production rules; blackboard; computational geometry; CAD/CAM; computational geometry; machining; pattern recognition; planning (artificial intelligence); solid modelling; spatial reasoning

A. Requicha and J. Vandenbrande, "Spatial Reasoning for the Automatic Recognition of Machinable Features in Solid Models," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 15, no. , pp. 1269-1285, 1993.
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