With the state-of-the-art technologies, NC tool paths are optimized along the feed direction of the tool path without the consideration of the consistency in the crossing (step-over) direction. As a result, the surface finishing is not fully optimal. In this paper, a method that performs the feed rate scheduling with consistency in crossing direction is proposed. The core of the method involves three steps: cross-directional information reconstruction, tool-path feature curve construction, and nominal feed rate computation. To reconstruct the cross-directional information, the neighbor projections, which are the nearest points on the adjacent pass segments of each GOTO point, are computed. For feature curve construction, feature points of the tool path are identified and then connected into curves along the crossing direction based on the neighbor projection information. The tool path is then divided according to the feature curves into feed rate intervals. The nominal feed rate of each feed rate interval is computed and blended with the nominal feed rates of the crossing neighbors, to achieve the consistency in the crossing direction. Information on the nominal feed rates and feature points is sent to the CNC to compute the final feed rate scheduling that takes advantages of the cross-consistent nominal feed rates. The proposed method is implemented in a lab-developed software program and validated experimentally using a commercial CNC. Experiments and simulations on two workpieces verify the effectiveness of the proposed cross-directional feed rate optimization method.
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The authors acknowledge the help of Chenglei Zhang and Zhiwei Su.
This study received support from the National Natural Science Foundation of China (51575386).
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Lee, C., Yang, F., Zhou, H. et al. Cross-directional feed rate optimization using tool-path surface. Int J Adv Manuf Technol 108, 2645–2660 (2020). https://doi.org/10.1007/s00170-020-05336-4
- CNC machining
- Tool-path surface
- Feature curve identification
- Feed rate scheduling
- Cross-directional optimization