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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
Industry 4.0
Acoustic emission testing
Cutting tools
Industry 4.0
Wear of materials
Current sensors
Data driven
Manufacturing efficiency
Products quality
Recent trends
Tool wear
Tool wear monitoring
Wear prediction
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
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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