Educational Software for Force and Roughness Prediction in Turning Operations based on Neural Networks

S.L.R. Almeida, M. Stipkovic, and O. Novaski (Brazil)


artificial neural networks, machining, force and roughness, simulation, CNC


This paper reports the development of a module for force and surface roughness estimation as a part of educational software which is able to simulate the most common turning processes, based on CNC technology. It targets becoming an auxiliary tool on professional labor training (engineers or technicians) in optimized machining process planning. Besides the conventional theoretical models, the software will implement an artificial neural network, an AI technique which is largely used in empiric problems to make prediction. The first results shows that the ANN model is very accurate and can approximate with reasonable confidence the experimental results.

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