Mechanical Engineering Commons^™

Analysis And Modeling Of Depth-Of-Cut During End Milling Of Deposited Material, Haythem Gaja

Masters Theses

"This study addresses depth-of-cut detection and tool-workpiece engagement using an acoustic emission monitoring system during milling machining for a deposited material. Online detection of depth-of-cut presents many technical difficulties. Researchers have used various types of sensors and methods to assess the depth-of-cut and surface errors. Due to the strong correlation between acoustic emission and cutting depth during the depth end milling process, it is useful to forecast the depth-of-cut from the acoustic emission signal. This work used regression analysis to model and detect the depth-of-cut. The experiments were carried out on a Fadal vertical 5-Axis computer numerical control machine using …