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Prediction of bending parameters and automated operation planning for sheet-metal bending orientated to graphical programming

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Abstract

The core of graphical programming for sheet-metal bending is operation planning based on parameter identification, which can directly determine the bending quality and efficiency. Given this, the proposed graphical programming system and method can predict the inner arc radius of bending oriented to programming demands and optimize multi-step bending operations. At first, a neural network model based on multi-layer perceptron (MLP) was established, considering the number of neurons and hidden layers. In the bending process a fitness function was defined, and the discrete particle swarm optimization (DPSO) was improved using the adaptive inertia weight and the genetic algorithm (GA). Finally, the operation planning of 10-step and 20-step bending was simulated, and bending tests were conducted on sheet-metal workpieces for verification. The results show that the algorithm’s maximum positive error and minimum negative error in predicting the arc radius are 0.12 mm and − 0.16 mm, respectively. When there are 10 bending steps, the particle swarm optimization-genetic algorithm (PSO-GA) converges after only ten evolutions; when the bending steps increase to 20, the fitness value finally stabilizes at 1.31. The optimal operations of the experimental six-step bending part are 6 → 5 → 4 → 3 → 1 → 2. This result indicates that the workpiece is turned over three times and turned around once in the sheet-metal bending process, which is consistent with the simulation, thus verifying the bending efficiency and accuracy.

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Funding

This work is supported by the National Natural Science Foundation of China (52175100, 52205568), 333 High-level Talents Training Project (2022–3-16–343), and the Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications (Grant No. NY221123).

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Authors and Affiliations

  1. College of Automation, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China

    Fengyu Xu, Dawei Ding, Baojie Fan & Sen Yang

  2. Jiangsu Engineering Research Center for IOT Intelligent Robots, Nanjing, China

    Fengyu Xu, Dawei Ding, Baojie Fan & Sen Yang

Authors
  1. Fengyu Xu
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  2. Dawei Ding
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  3. Baojie Fan
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  4. Sen Yang
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Contributions

All authors contributed to the study conception and design. System development, data collection, experiment, and analysis were performed by FX, DD, BF, and SY. The first draft of the manuscript was written by FX, and all authors commented on the previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Fengyu Xu.

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Xu, F., Ding, D., Fan, B. et al. Prediction of bending parameters and automated operation planning for sheet-metal bending orientated to graphical programming. Int J Adv Manuf Technol 126, 2191–2204 (2023). https://doi.org/10.1007/s00170-023-11271-x

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  • DOI: https://doi.org/10.1007/s00170-023-11271-x

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