Proceedings of the 2nd International Conference on Innovation in Information Technology and Business (ICIITB 2024)

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Exploring the Benefits of Integrating Machine Learning and Tool Condition Monitoring for Manufacturing Applications

Authors
S. Gokul1, S. A. Vigneshvar1, R. Ashwathi Krishna1, K. Kabilan1, P. Vijaya2, *
1Department of Mechanical Engineering, Sri Eshwar College of Engineering, Coimbatore, 641202, Tamil Nadu, India
2Department of Mathematics and Computer Science, Modern College of Business and Science, Bowshar, Muscat, Sultanate of Oman
*Corresponding author. Email: pvvijaya@gmail.com
Corresponding Author
P. Vijaya
Available Online 23 August 2024.
DOI
10.2991/978-94-6463-482-2_4How to use a DOI?
Keywords
Machine Learning; Tool Condition Monitoring; Manufacturing Applications; Process Control; Downtime; Integration
Abstract

This review article explores the potential benefits of integrating machine learning and tool condition monitoring for manufacturing applications. It first reviews the current state of machine learning and tool condition monitoring and their respective applications in manufacturing. It then discusses the potential benefits of combining the two, including improved process control and reduced downtime, as well as the challenges associated with integrating the two technologies. Finally, the review article provides an overview of existing approaches to integrating machine learning and tool condition monitoring, examining the advantages and drawbacks of each. The article concludes with a summary of the key findings and implications for the future of integrating machine learning and tool condition monitoring in manufacturing. The article provides a comprehensive overview of the benefits and challenges associated with integrating machine learning and tool condition monitoring, as well as a review of existing approaches and future implications.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2nd International Conference on Innovation in Information Technology and Business (ICIITB 2024)
Series
Advances in Computer Science Research
Publication Date
23 August 2024
ISBN
978-94-6463-482-2
ISSN
2352-538X
DOI
10.2991/978-94-6463-482-2_4How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - S. Gokul
AU  - S. A. Vigneshvar
AU  - R. Ashwathi Krishna
AU  - K. Kabilan
AU  - P. Vijaya
PY  - 2024
DA  - 2024/08/23
TI  - Exploring the Benefits of Integrating Machine Learning and Tool Condition Monitoring for Manufacturing Applications
BT  - Proceedings of the 2nd International Conference on Innovation in Information Technology and Business (ICIITB 2024)
PB  - Atlantis Press
SP  - 38
EP  - 53
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-482-2_4
DO  - 10.2991/978-94-6463-482-2_4
ID  - Gokul2024
ER  -