Numerical Validation for End Milling Machine Parameter Optimization of AA 6041 Using Python

In manufacturing, machining efficiency is critical to reduce waste, rejects, and maintaining high standards of operations. This paper presents works on material testing for aluminum alloy (AA) 6041 that employed the end milling operation using a HAAS three-axis CNC milling machine with uncoated carbide end mill in dry conditions. Machining parameters studied for optimal cutting parameters were cutting speed ( \(V_c\) ), feeding speed ( \(V_f\) ), and depth of cut ( \(D_{oc}\) ). The response of this process produced three dependent factors, namely the surface roughness ( \(R_a\) ), cutting temperature ( \(T_c\) ), and cutting force ( \(F_c\) ). The response was validated against machining results of the end milling process using three runs for each cutting parameter. These were performed using Python with the mathematical model of ANOVA. Results obtained indicated prediction values of \(R_a\) at 0.135 \(\mu \) m, \(T_c\) at \(29.30^\circ \) , and \(F_c\) equaled 7 N. These responses showed near identical values with the experimental results.