Abstract
Nowadays, Computerized numerical control (CNC) machines are widely used to manufacture products. However, some tasks of the machining process are not completely automated; moreover, older machines does not have specific communication ports. This project proposes to optimize the setup of workpiece zero point, a very important task for referencing the workpiece. Artificial vision technology was used to automate micro-movements required to find the coordinates (x, y, z) of the workpiece origin (W) with respect to the absolute machine origin (M). The implemented device captures the image of the workpiece, and the interface (GUI) performs the computerized treatment of the image to obtain the coordinates of the workpiece zero point (W). Finally, a G code program with the coordinates is sent to the machine for registration at the offset setting function. The project is developed in a FADAL VMC 3016 machining center with a FANUC 18i-M control, model 2006, which was chosen for the case study. The results were a reduction of average setup time from 8.18 to 1.89 min and average absolute error on the accuracy of 0.495 mm.
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Robalino Pinango, A., Culqui Culqui, B. (2021). Optimization of the Setup of Workpiece Zero Point in a Numerical Control Machine with an Artificial Vision System. In: Botto Tobar, M., Cruz, H., Díaz Cadena, A. (eds) Recent Advances in Electrical Engineering, Electronics and Energy. CIT 2020. Lecture Notes in Electrical Engineering, vol 763. Springer, Cham. https://doi.org/10.1007/978-3-030-72212-8_10
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