DefinePK

Abstract

This paper discusses the findings on the analysis of surface roughness with the acoustic emission (AE) produced during end milling process. Different parameters were chosen for each experiment, namely cutting speed, feed rate and depth of cut. All data collected from the AE sensor were captured using AEWin software and later analyzed in MATLAB software. Fast Fourier Transform (FFT) method was used for data analysis to convert time domain into frequency domain signal, allowing the RMS, amplitude and frequency to be calculated. The results indicate that the most influential parameter to the surface roughness are firstly feed rate, followed by cutting speed, and finally depth of cut. It is found that as cutting speed increases, the surface roughness decreases with a higher amplitude of RMS signal. In case of increasing feed rate, the surface roughness increases with a higher amplitude of RMS signal. Lastly, increasing the depth of cut shows negligible effect towards the surface roughness and amplitude of RMS. The result have shown that the AE components responded effectively to the changes of occurrences in milling process with respect to specimen’s surface roughness.