Development of Artificial Neural Network models for vibration classification in machining process on Brownfield CNC machining center - Stepanić, Pavle; Dučić, Nedeljko; Stanković, Nebojša (Journal of Production Engineering, 2024)
This study presents the development of artificial neural network models capable of classifying the type of vibration during the step drilling process. Classification refers to recognizing the nature of vibrations during the machining process and categorizing them into two classes: safe and harmful. The data used in the study were obtained from Bosch and collected during the aforementioned machining process on a four-axis horizontal CNC machining center. Several different architectures of artificial neural networks have been developed, and their performance (with a classification success rate of around 96%) has shown that they can be applied as a highly useful tool in predictive maintenance.