STEP-based feature recognition for manufacturing cost optimization

This paper proposes to integrate feature recognition and process planning in the machining domain. The input part is analyzed to produce a set of setups which might he needed to manufacture the part. Then, a two-layered search strategy is adopted, where a node of the upper layer corresponds to a specific setup, and a node of the lower layer corresponds to a specific process for a feature. For each visited setup node, tool database is consulted in order to generate manufacturable features, feature dependencies are established, and the lower layer search is invoked. The lower layer computes an optimal machining sequence and its manufacturing cost. Then, the control gets returned to the upper layer. Together with the manufacturing cost computed at the lower layer, setup cost analysis guides the upper layer's setup space search. Eventually, a setup sequence is generated where an optimal machining sequence is determined per each setup. The system presented in this paper uses STEP as input and output formats, and therefore can be ported to arbitrary CAD and planning systems. (C) 2001 Elsevier Science Ltd. Ah rights reserved.