Abstract:
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Roughness obtained in honing process depends on many different process parameters, such as grain
size of abrasive stones, pressure of stones on the workpiece’s surface, density of abrasive, tangential
speed of the honing head and linear speed of the honing head. This fact makes it difficult to study the
process from an analytical point of view. For this reason, use of empirical methods or use of artificial
intelligence is recommended in this case. In the present paper, results about use of neural networks for
obtaining average roughness Ra as a function of honing parameters are presented. Best neural
network was chosen among different possibilities. For doing this, experimental results were divided
into three groups: 70 % of results were used for training, 15 % of results were used for validation and
15 % of results were used as test to compare networks with other models. The best neural network was
considered to be the one with lowest errors using the validation experimental results. |