Study on In-Situ Tool Wear Detection during Micro End Milling Based on Machine Vision

Article Multidisciplinary Sciences

Integrating object detection and image segmentation for detecting the tool wear area on stitched image

Wan-Ju Lin et al.

Summary: A novel flank wear detection method combining template matching and deep learning techniques was proposed in this study, with U-Net model achieving the best performance in extracting tool wear areas. The predicted wear areas can determine the frequency of tool changes based on the curve of tool wear.

SCIENTIFIC REPORTS (2021)

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Article Multidisciplinary Sciences

Digital Twin-Driven Tool Wear Monitoring and Predicting Method for the Turning Process

Kejia Zhuang et al.

Summary: This study presents a method based on Digital Twin (DT) to achieve high precision in monitoring and predicting tool wear. The framework of the cutting tool system DT is designed, key enabling technologies are elaborated, and a case study of the turning process is presented to verify the feasibility of the framework.

SYMMETRY-BASEL (2021)

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Proceedings Paper Materials Science, Multidisciplinary

Optimization of cutting temperature in machining of titanium alloy using Response Surface Method, Genetic Algorithm and Taguchi method

Bhagyashree Jayarjun Kadam et al.

Summary: This study utilized Finite Element Modeling to predict cutting tool temperature during turning of Titanium alloy Ti-6Al-4 V under dry machining, and conducted Response Surface Method (RSM) and Taguchi analysis. The experimental results showed that cutting speed of 120 m/min, feed rate of 0.10 mm/rev, and depth of cut of 0.5 mm are desirable for obtaining optimal conditions.

MATERIALS TODAY-PROCEEDINGS (2021)

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Proceedings Paper Engineering, Multidisciplinary

Identification of tool wear status and correlation of chip morphology in micro-end milling of mild steel (SAE 1017) using acoustic emission signal

M. Prakash et al.

3RD INTERNATIONAL CONFERENCE ON ADVANCES IN MECHANICAL ENGINEERING (ICAME 2020), PTS 1-6 (2020)

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Article Automation & Control Systems

A novel algorithm for tool wear online inspection based on machine vision

Qiulin Hou et al.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2019)

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Article Engineering, Multidisciplinary

A machine vision system for micro-milling tool condition monitoring

Yiquan Dai et al.

PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY (2018)

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Article Automation & Control Systems

The influences of tool wear on Ti6Al4V cutting temperature and burn defect

S. C. Sui et al.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2016)

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Study on In-Situ Tool Wear Detection during Micro End Milling Based on Machine Vision

Related references

Integrating object detection and image segmentation for detecting the tool wear area on stitched image

Digital Twin-Driven Tool Wear Monitoring and Predicting Method for the Turning Process

Optimization of cutting temperature in machining of titanium alloy using Response Surface Method, Genetic Algorithm and Taguchi method

Identification of tool wear status and correlation of chip morphology in micro-end milling of mild steel (SAE 1017) using acoustic emission signal

A novel algorithm for tool wear online inspection based on machine vision

A machine vision system for micro-milling tool condition monitoring

The influences of tool wear on Ti6Al4V cutting temperature and burn defect

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