FEATURE-BASED MACHINING SEQUENCE GENERATION INTEGRATED WITH SETUP PLANNING

摘要

Despite the long history of research on feature recognition, the impact of features technology has been illusive and its research results have rarely been transferred into industry. One of the reasons is the separation of feature recognition and process planning. This paper proposes to integrate the two activities in the machining domain, and presents efforts towards it. The system presented in this paper has been built on the well-known feature recognizer IF{sup}2 (Integrated Incremental Feature Finder). The solid model of the input part is analyzed to produce a set of setups which might be needed to manufacture the part. Then, a two-layered search strategy based on A{sup}* algorithm 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. The upper layer's setup nodes are visited one at a time. For each visited setup node, all features manufacturable in the setup are recognized and the lower layer search is invoked to produce the optimal machining sequence among the features. Tool database is consulted in order to generate manufacturable features, and dependencies among the manufacturable features are established through geometric reasoning. Eventually, a feature-based optimal machining sequence and its manufacturing cost are computed with the aid of a machining cost function. When an optimal machining sequence is generated, the control gets returned to the upper layer search. 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. This paper focuses on the upper layer search.