Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/9090
Title: | A Review: Sensors Used in Tool Wear Monitoring and Prediction | Authors: | Ünal P. Deveci B.U. Özbayoglu A.M. |
Keywords: | Accelerometer Acoustic emission Current sensor Dynamometer Industry 4.0 Microphone Sensors Acoustic emission testing Cutting tools Industry 4.0 Wear of materials Acoustic-emissions Computer-aided Current sensors Data driven Manufacturing efficiency Products quality Recent trends Tool wear Tool wear monitoring Wear prediction Forecasting |
Publisher: | Springer Science and Business Media Deutschland GmbH | Abstract: | Tool wear prediction/monitoring of CNCs is crucial for improving manufacturing efficiency, guaranteeing product quality, and minimizing tool costs. As a computer-aided application, it has a significant role in the future and development of Industry 4.0. Sensors are the key piece of hardware used by data-driven enterprises to predict/monitor tool wear. The purpose of this study is to inform about the predominant types of sensors used for tool wear monitoring/prediction. This study serves as a resource for researchers and manufacturers by providing the recent trends in sensors for tool wear monitoring. Thus, it may help reduce the time spent on sensor selection. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. | Description: | 18th International Conference on Mobile Web and Intelligent Information Systems, MobiWIS 2022 -- 22 August 2022 through 24 August 2022 -- -- 281999 | URI: | https://doi.org/10.1007/978-3-031-14391-5_15 https://hdl.handle.net/20.500.11851/9090 |
ISBN: | 9.78303E+12 | ISSN: | 0302-9743 |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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