MATEC Web Conf.
Volume 252, 2019III International Conference of Computational Methods in Engineering Science (CMES’18)
|Number of page(s)||6|
|Section||Computational Artificial Intelligence|
|Published online||14 January 2019|
Implementation of artificial intelligence in optimisation of technological processes
Lublin University of Technology, Management Faculty, Poland
2 Lublin University of Technology, Mechanical Engineering Faculty, Poland
* Corresponding author: firstname.lastname@example.org
This article introduces an algorithm for determining optimal parameters of a technological process. The objective function is the processing time of operations (efficiency) at the constraint of quality requirements of finish according to the designer specification. The problem of selecting a correct combination of processing parameters may only be solved when the cause-and-effect relationship between the finish quality and the machining settings is known. If the process considered for optimisation is repeatable, it appears economically viable to invest resources in the development of a model that would describe these relationships. To this end, we propose employing the artificial neural network trained on the progressions obtained from the tests. In the second stage, the Multiple-Input-Multiple-Output (MIMO) system, capable of representing relationships of nonlinear nature, was implemented for the optimisation of the objective function. The paper presents the application of the developed algorithm in determination of optimal parameters for the roller burnishing process of surface treatment. A technologist/software user defines the range of acceptable surface finishes. The optimisation algorithm determines a set of modifiable parameters that ensure minimal processing time at a specified surface finish requirements constraint.
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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