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.
Özbayoğlu 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
Issue Date: 2022
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:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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