Abstract

CURRA-SOSA, Dagnier Antonio et al. Assessment of the specific energy consumption in high speed turning of AISI-1045 steel using neural networks. Ingeniería Mecánica [online]. 2020, vol.23, n.2  Epub Aug 01, 2020. ISSN 1815-5944.

This article estimates the specific energy consumption in high-speed dry turning of AISI 1045 steel, using neural networks. Various artificial neural network architectures of the multilayer perceptron type were used to establish the relationships between the parameters of the cutting regime and the technological indices of machining. The following were considered as input values for the neural network models: the cutting speed, the test duration, the machining time, the number of passes and the position of the cutting tool on the specimen. The selected neural network model was the best, based on the mean square error and the regression coefficient R2, reflecting good precision in the approximation. The results showed a good level of reliability in predicting specific energy consumption under various machining conditions.

Keywords : specific energy consumption; high-speed dry turning; AISI 1045; artificial neural network.

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