Abstract
In order to ensure the accuracy and efficiency of sheet metal bending, a more efficient bending process planning algorithm is required. First of all, under the premise of comprehensively considering interference discrimination and efficiency guarantee, this paper establishes the fitness function of the process planning problem, and converts the process of selecting the optimal process into a problem of solving the optimal solution of the function. Then, since Particle Swarm optimization is easy to fall into the local optimal solution, an improved algorithm is proposed to solve the optimal process. Finally, the optimal bending process of sheet metal parts with different complexity is solved by experiments. The results show that the improved algorithm can calculate the optimal or nearly optimal results within a reasonable time range when there are more bending steps.
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Acknowledgment
This research is supported by the National Natural Science Foundation of China (51775284), the Primary Research & Development Plan of Jiangsu Province (BE2018734), the Natural Science Foundation of Jiangsu Province (BK20201379), and Six Talent Peaks Project in Jiangsu Province (JY-081).
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Sen, Y., Ma, K., Yi, Z., Xu, F. (2021). A Research on Bending Process Planning Based on Improved Particle Swarm Optimization. In: Liu, XJ., Nie, Z., Yu, J., Xie, F., Song, R. (eds) Intelligent Robotics and Applications. ICIRA 2021. Lecture Notes in Computer Science(), vol 13013. Springer, Cham. https://doi.org/10.1007/978-3-030-89095-7_34
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DOI: https://doi.org/10.1007/978-3-030-89095-7_34
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