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: Unal, Perin
Deveci, Bilgin Umut
Ozbayoglu, Ahmet Murat
Keywords: Sensors
Industry 4.0
Accelerometer
Acoustic Emission
Microphone
Current Sensor
Dynamometer
Publisher: Springer International Publishing Ag
Series/Report no.: Lecture Notes in Computer Science
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.
Description: Deveci, Bilgin Umut/0000-0002-0644-0782; Unal, Perin/0000-0003-1357-2430; Ozbayoglu, Murat/0000-0001-7998-5735
URI: https://doi.org/10.1007/978-3-031-14391-5_15
ISBN: 9783031143915
9783031143908
ISSN: 0302-9743
1611-3349
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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