Abstract
In this study, the burr and slot widths formed after the micro-milling process of Inconel 718 alloy were investigated using a rapid and accurate image processing method. The measurements were obtained using a user-defined subroutine for image processing. To determine the accuracy of the developed imaging process technique, the automated measurement results were compared against results measured using a manual measurement method. For the cutting experiments, Inconel 718 alloy was machined using several cutting tools with different geometry, such as the helix angle, axial rake angle, and number of cutting edges. The images of the burr and slots were captured using a scanning electron microscope (SEM). The captured images were processed with computer vision software, which was written in C++ programming language and open-sourced computer library (Open CV). According to the results, it was determined that there is a good correlation between automated and manual measurements of slot and burr widths. The accuracy of the proposed method is above 91%, 98%, and 99% for up milling, down milling, and slot measurements, respectively. The conducted study offers a user-friendly, fast, and accurate solution using computer vision (CV) technology by requiring only one SEM image as input to characterize slot and burr formation.
Highlights
User abilities and diligence are important parameters to obtain an accurate result from the scanning electron microscope (SEM) images
In another study implemented by Tuiran et al [39], the burrs resulting from micro-milling were analyzed with the help of an image processing technology, and the accuracy was found to be around 84.46%, which gives the correlation between the spindle speed and burr formation
Today, computer vision (CV) is a widely used technology in many fields. Applying this technology by processing still SEM images directly without additional steps offers an easy, user-friendly, fast, and accurate solution while eliminating the additional skills required for measuring SEM images
Summary
User abilities and diligence are important parameters to obtain an accurate result from the SEM images In this field, there are limited studies and resources to extract data from still images using CV technology, which is used for evaluating milling burr formation. There are limited studies and resources to extract data from still images using CV technology, which is used for evaluating milling burr formation Applying this technology to process still SEM images directly without additional steps offers an easy and effective solution while eliminating additional skills required for measuring SEM images. The present study offers a fast and user-friendly solution for measuring slot and burr formation at the micro-scale as well as requiring only one SEM image as input to characterize slot and burr formation with high accuracy. The approach offered here is an accurate and robust method for precisely measuring slot and burr widths and can be used for slot and burr evaluation in micro-machining applications in the research and industry domains
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
