STEP-based feature recognition for manufacturing cost optimization

This paper proposes to integrate feature recognition and process planning i n the machining domain. The input part is analyzed to produce a set of setu ps which might he needed to manufacture the part. Then, a two-layered searc h strategy is adopted, where a node of the upper layer corresponds to a spe cific setup, and a node of the lower layer corresponds to a specific proces s for a feature. For each visited setup node, tool database is consulted in order to generate manufacturable features, feature dependencies are establ ished, and the lower layer search is invoked. The lower layer computes an o ptimal machining sequence and its manufacturing cost. Then, the control get s returned to the upper layer. Together with the manufacturing cost compute d at the lower layer, setup cost analysis guides the upper layer's setup sp ace search. Eventually, a setup sequence is generated where an optimal mach ining sequence is determined per each setup. The system presented in this p aper uses STEP as input and output formats, and therefore can be ported to arbitrary CAD and planning systems. (C) 2001 Elsevier Science Ltd. Ah right s reserved.