| Issue |
MATEC Web Conf.
Volume 299, 2019
Modern Technologies in Manufacturing (MTeM 2019)
|
|
|---|---|---|
| Article Number | 04003 | |
| Number of page(s) | 6 | |
| Section | Machining Processes and Quality Assurance | |
| DOI | https://doi.org/10.1051/matecconf/201929904003 | |
| Published online | 02 December 2019 | |
Use of Neural Networks in Tool Wear Prediction
1
Technical University of Košice, Faculty of Manufacturing Technologies,
080 01,
Prešov,
Slovakia
2
Intemac Solutions,
s.r.o., Blanenská 1288/27,
664 34,
Kuřim,
Czech Republic
* Corresponding author: marek.kocisko@tuke.sk
Modern CNC machine tools include a number of sensors that collect machine status data. These data are used to control the production process and for control of the CNC machine status. No less importantpart of the production process is also a machine tool. The condition of the cutting tool is important for the production quality and its failure can cause serious problems. Monitoring the condition of thecutting tool is complicated due to its dimensions and working conditions. The article describes how the tool wear can be predicted from the measured values of vibration and pressure by using neural networks.
© 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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