Journal of Production Engineering

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Vol. 27 No. 2 (2024)
Original Research Article

Development of Artificial Neural Network models for vibration classification in machining process on Brownfield CNC machining center

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  • Pavle Stepanić,
  • Nedeljko Dučić,
  • Nebojša Stanković
Pavle Stepanić
Lola Institute Ltd: Belgrade, RS
Nedeljko Dučić
Faculty of Technical Sciences Čačak, University of Kragujevac
Nebojša Stanković
Faculty of Technical Sciences Čačak, University of Kragujevac
DOI: https://doi.org/10.24867/JPE-2024-02-016

Published 2024-09-13

abstract views: 46 // FULL TEXT ARTICLE (PDF): 0


Keywords

  • smart maintenance,
  • vibration,
  • drilling,
  • Artificial neural networks

How to Cite

Stepanić, Pavle, Nedeljko Dučić, and Nebojša Stanković. 2024. “Development of Artificial Neural Network Models for Vibration Classification in Machining Process on Brownfield CNC Machining Center”. Journal of Production Engineering 27 (2):16-20. https://doi.org/10.24867/JPE-2024-02-016.

Copyright (c) 2024 Journal of Production Engineering

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

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.

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