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A Review: Sensors Used in Tool Wear Monitoring and Prediction

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Mobile Web and Intelligent Information Systems (MobiWIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13475))

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.

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Authors and Affiliations

  1. TEKNOPAR Industrial Automation, İvedikosb Yenimahalle, 06378, Ankara, Turkey

    Perin Ünal & Bilgin Umut Deveci

  2. TOBB University of Economics and Technology, Söğütözü Çankaya, 06510, Ankara, Turkey

    Ahmet Murat Özbayoğlu

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  1. Perin Ünal
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  2. Bilgin Umut Deveci
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  3. Ahmet Murat Özbayoğlu
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Correspondence to Perin Ünal .

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Editors and Affiliations

  1. University of Bradford, Bradford, UK

    Irfan Awan

  2. Oxford Brookes University, Oxford, UK

    Muhammad Younas

  3. Lodz University of Technology, Lodz, Poland

    Aneta Poniszewska-Marańda

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Ünal, P., Deveci, B.U., Özbayoğlu, A.M. (2022). A Review: Sensors Used in Tool Wear Monitoring and Prediction. In: Awan, I., Younas, M., Poniszewska-Marańda, A. (eds) Mobile Web and Intelligent Information Systems. MobiWIS 2022. Lecture Notes in Computer Science, vol 13475. Springer, Cham. https://doi.org/10.1007/978-3-031-14391-5_15

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  • DOI: https://doi.org/10.1007/978-3-031-14391-5_15

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