Sound-based monitoring of CNC machining operations and detection of machine tool degradation
CNC machining operations are an essential part of modern manufacturing, with applications spanning various industries from automotive and aerospace to medical devices. Monitoring the machine and detecting CNC tool degradation is crucial for ensuring the quality of the machined parts and preventing catastrophic failures that can lead to costly downtime. Neuron Soundware (NSW) has successfully explored the use of sound-based monitoring for detecting machine tool degradation in CNC machining operations, in the process enhancing manufacturing efficiency and sustainability.
By analysing the sound signals generated during the machining process, NSW can accurately identify anomalies and assess the condition of the machine tools. The use of sound-based monitoring methods, as developed by NSW, is gaining traction, demonstrating their effectiveness in detecting tool wear, crack propagation, and other forms of degradation.
NSW has worked extensively on the relationship between sound signal and tool wear under multiple machining conditions, and has developed regression and artificial neural network models to predict the degree of tool wear. The results achieved show that the NSW method maintains prediction accuracy regardless of the different machining conditions, achieving accuracy higher than 87%.
NSW is investing a lot of effort into this process of sound-based monitoring for detecting machine tool degradation in CNC machining operations. Pavel Konecny, the founder and CEO of Neuron Soundware said: “By analysing the sound signals generated during the machining process, we can identify anomalies and assess the condition of the machine tools, enabling proactive maintenance and preventing costly downtime. As the manufacturing industry continues to evolve, the integration of sound-based monitoring in CNC machining operations is expected to play a crucial role in enhancing manufacturing efficiency and sustainability.”
Recent Posts
