Process planning is an important stage in the manufacturing process because it bridges the gap between design and manufacture. Automation of this crucial activity will yield significant benefits in the efficiency, consistency and economy of manufacture. In this paper, an AI-based approach to the automation of process planning is described. It explores the potential for generating efficient plans for machining operations by making use of techniques from AI research. Currently, the system is capable of generating process plans for rotational parts. We plan to extend it to examine 2 1 2-D and 3-D machining of prismatic parts for generality. The planner selects processes and tools and generates a complete operation sequence. Detailed schemes for feature-based part representation and tool description enable us to include relative tolerance information, which is a distinguishing characteristic of this system. The plan synthesized by the system can be further processed to generate NC code. The system described in this paper is characterized by the following: • • Use of a feature-based representation system. • • Accessibility to IGES format input commercial CAD systems. • • Complete tool description scheme for checking geometric consistency during tool selection. • • Adoption of the hierarchical planning approach and utilizing the nonlinear planning algorithm in implementation. © 1995.
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