MATEC Web Conf.
Volume 112, 201721st Innovative Manufacturing Engineering & Energy International Conference – IManE&E 2017
|Number of page(s)||6|
|Section||Flexible Manufacturing, Automation and Robotics in Technological Processes|
|Published online||03 July 2017|
The estimation with Artificial Neural Networks of some quality parameters for the surfaces processed by superfinishing
1 University of Pitesti, Department of Manufacturing and Industrial Management, Tg. din Vale Str., no.1, Pitesti, Romania Romania
2 University of Pitesti, Department of Electronics, Computers, Communications and Electrical Engineering, Tg. din Vale Str., no.1, Pitesti, Romania
* Corresponding author: email@example.com
This paper presents a study on the quality parameters obtained by superfinishing. The quality is characterized by the roughness. They are dependent on the following process parameters: circular feed, the contact pressure between the piece and the tool, frequency of oscillation of the tool, the coverage degree between the tool and the piece and the basic time. Because the dependence between inputs and outputs is a nonlinear one, in this paper we used an artificial feed forward neural network (ANN). The ANN is trained with the backpropagation algorithm, using as training patterns data measured from the mechanical process. The ANN is used to estimate some parameters from future experiments of the mechanical process.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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