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.
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Use of Neural Networks in Tool Wear Prediction
Semantic Scholar · Engineering · 2019
Abstract
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.
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