Optimización de parámetros de CNC de acuerdo a criterios de productividad usando un modelo de máquina basado en redes neuronales
- Javier Arenas-lópez 1
- Rosa Basagoiti-Astigarraga 2
- Maite Beamurgia-Bengoa 1
- Jorge Martínez de Alegría-Sáenz de Castillo 1
- 1 Fagor Aotek. Eskoriatza. Gipuzkoa. España
- 2 Escuela Polotécnica de Mondragón. Depto. Electrónica e Informática. Mondragón. Gipuzkoa. España
ISSN: 0012-7361, 0012-7361
Year of publication: 2020
Volume: 95
Issue: 5
Pages: 514-519
Type: Article
More publications in: Revista DYNA
Abstract
Every machine-tool user wants to maximize the productivity of their machines looking for balance between speed, precision and lifetime of mechanical components. Nevertheless, because CNCs have wide-ranging use, their correct parametrization for each case is key to achieving the desired objectives; on the other hand, minimizing the numbers of experimental tests to be performed on the machine is essential to reduce time and costs of the set-up process. In order to solve both difficulties, this paper presents a tool to give final user necessary information to properly adjust CNC parameters according to productivity criteria. The method makes use of experimental data to obtain a model of the machine based on neural networks. With this model machining time, geometric error and smoothness of any piece to be manufactured can be predicted, and therefore minimizing test on the real machine and recommending the appropriate values for the CNC.