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Review

A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends

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Mechanical Engineering Department, Technology Faculty, Selcuk University, Selçuklu, 42130 Konya, Turkey
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Mechanical Engineering Department, Engineering and Architecture Faculty, Selcuk University, Akşehir, 42130 Konya, Turkey
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Department of Automated Mechanical Engineering, South Ural State University, Lenin Prosp. 76, 454080 Chelyabinsk, Russia
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Mechanical Engineering Department, Engineering and Architecture Faculty, Bingöl University, 12000 Bingöl, Turkey
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Department of Metallurgical and Materials Engineering, Selcuk University, Selçuklu, 42130 Konya, Turkey
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Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan 250100, China
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Department of Production Engineering, UTP University of Science and Technology, Al. Prof. S. Kaliskiego 7, 85-796 Bydgoszcz, Poland
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School of Mechanical and Design Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK
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Department of Production Engineering, Faculty of Mechanical Engineering, Koszalin University of Technology, Racławicka 15-17, 75-620 Koszalin, Poland
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Department of Mechanical Engineering, IKG Punjab Technical University, Jalandhar-Kapurthala Road, Kapurthala, Punjab 144603, India
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Author to whom correspondence should be addressed.
Sensors 2021, 21(1), 108; https://doi.org/10.3390/s21010108
Received: 28 November 2020 / Revised: 20 December 2020 / Accepted: 22 December 2020 / Published: 26 December 2020
The complex structure of turning aggravates obtaining the desired results in terms of tool wear and surface roughness. The existence of high temperature and pressure make difficult to reach and observe the cutting area. In-direct tool condition, monitoring systems provide tracking the condition of cutting tool via several released or converted energy types, namely, heat, acoustic emission, vibration, cutting forces and motor current. Tool wear inevitably progresses during metal cutting and has a relationship with these energy types. Indirect tool condition monitoring systems use sensors situated around the cutting area to state the wear condition of the cutting tool without intervention to cutting zone. In this study, sensors mostly used in indirect tool condition monitoring systems and their correlations between tool wear are reviewed to summarize the literature survey in this field for the last two decades. The reviews about tool condition monitoring systems in turning are very limited, and relationship between measured variables such as tool wear and vibration require a detailed analysis. In this work, the main aim is to discuss the effect of sensorial data on tool wear by considering previous published papers. As a computer aided electronic and mechanical support system, tool condition monitoring paves the way for machining industry and the future and development of Industry 4.0. View Full-Text
Keywords: indirect tool condition monitoring systems; turning; machining; vibration; cutting force; acoustic emission; temperature; current; industry 4.0 indirect tool condition monitoring systems; turning; machining; vibration; cutting force; acoustic emission; temperature; current; industry 4.0
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MDPI and ACS Style

Kuntoğlu, M.; Aslan, A.; Pimenov, D.Y.; Usca, Ü.A.; Salur, E.; Gupta, M.K.; Mikolajczyk, T.; Giasin, K.; Kapłonek, W.; Sharma, S. A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends. Sensors 2021, 21, 108. https://doi.org/10.3390/s21010108

AMA Style

Kuntoğlu M, Aslan A, Pimenov DY, Usca ÜA, Salur E, Gupta MK, Mikolajczyk T, Giasin K, Kapłonek W, Sharma S. A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends. Sensors. 2021; 21(1):108. https://doi.org/10.3390/s21010108

Chicago/Turabian Style

Kuntoğlu, Mustafa, Abdullah Aslan, Danil Y. Pimenov, Üsame A. Usca, Emin Salur, Munish K. Gupta, Tadeusz Mikolajczyk, Khaled Giasin, Wojciech Kapłonek, and Shubham Sharma. 2021. "A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends" Sensors 21, no. 1: 108. https://doi.org/10.3390/s21010108

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