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

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SENSORS
卷 21, 期 1, 页码 -

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MDPI
DOI: 10.3390/s21010108

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indirect tool condition monitoring systems; turning; machining; vibration; cutting force; acoustic emission; temperature; current; industry 4.0

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The indirect tool condition monitoring systems provide a way to track the condition of cutting tools through various energy types, without direct intervention in the cutting zone. This study reviews the sensors commonly used in indirect tool condition monitoring systems and their correlations with tool wear over the past two decades, highlighting the limited research on tool condition monitoring systems in turning and the need for detailed analysis of measured variables such as tool wear and vibration. Tool condition monitoring is essential for the development of Industry 4.0 in machining industry, paving the way for future advancements.
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.

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