Journal of Production Engineering

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Vol. 25 No. 1 (2022)
Original Research Article

Application of cloud-based machine learning in cutting tool condition monitoring

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  • Mijodrag Milošević,
  • Dejan Lukić,
  • Gordana Ostojić,
  • Milovan Lazarević,
  • Aco Antić
Mijodrag Milošević
University of Novi Sad, Faculty of Technical Sciences, Departman for Production Engineering, Trg Dositeja Obradovica 6, 21000 Novi Sad, Serbia
Dejan Lukić
University of Novi Sad, Faculty of Technical Sciences, Departman for Production Engineering, Trg Dositeja Obradovica 6, 21000 Novi Sad, Serbia
DOI: https://doi.org/10.24867/JPE-2022-01-020

Published 2022-06-30

abstract views: 96 // FULL TEXT ARTICLE (PDF): 33


Keywords

  • Cloud manufacturing,
  • machine learning,
  • I 4.0,
  • smart maintenance,
  • condition monitoring

How to Cite

Milošević, M., Lukić, D., Ostojić, G., Lazarević, M., & Antić, A. (2022). Application of cloud-based machine learning in cutting tool condition monitoring. Journal of Production Engineering, 25(1), 20–24. https://doi.org/10.24867/JPE-2022-01-020

Copyright (c) 2023 Journal of Production Engineering

Creative Commons License

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

Abstract

One of the primary technologies in the Industry 4.0 concept refers to Smart maintenance or predictive maintenance that includes continuous or periodic sensor monitoring of physical changes in the condition of manufacturing resources (Condition monitoring). In this way, production delays or failures are timely prevented or minimized. In this context, the paper present a developed cloud-based system for monitoring the condition of cutting tool wear by measuring vibration. This system applies a machine learning method that is integrated within the MS Azure cloud system. The verification was performed on the data of the calculated central moments during the turning process, for cutting tool inserts with different degrees of wear.

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FULL TEXT ARTICLE (PDF)