Mathematical Modeling and Optimization of Milling Parameters in AA 5083 Aluminum Alloy

Gökhan Başar,Funda Kahraman,Ganime Tuğba Önder

doi:10.26701/ems.537087

Abstract

In this study, the selection of optimal cutting parameters for face milling of 5083 aluminum was investigated in order to minimize the surface roughness. Effect of selected parameters on the surface roughness was analyzed by using analysis of variance (ANOVA). The mathematical model was developed to estimate surface roughness in face milling process by using Response Surface Methodology (RSM). Feed, spindle speed and depth of cut were selected as input variables. The statistical analysis indicated that feed and spindle speed have the most considerable influence on surface roughness. After developed mathematical model, Desirability Function Analysis (DFA) was performed to optimize the cutting parameters. The lowest value of surface roughness (0.41 µm) was acquired at a feed of 3008 mm/min, a spindle speed of 5981 rpm and a depth of cut of 0.54 mm.

Highlights

The main purpose of chip removal process is to achieve the desired geometric and dimensional tolerance and a precise surface on the workpiece
Machine parts with the desired dimensional tolerance and surface quality can be machined on planar, oblique, circular and various profile surfaces
The research offered a face-centered cubic design combined with response surface methodology (RSM) to develop a mathematical model to estimate surface roughness

Summary

INTRODUCTION

The main purpose of chip removal process is to achieve the desired geometric and dimensional tolerance and a precise surface on the workpiece. Fnides et al [8] used RSM and DFA based optimizations to find the optimum cutting conditions of minimum surface roughness and maximum material removal rate in face milling of AISI 1040 steel. Elkhabeery et al [17] investigated the influence of input variables on the surface roughness, cutting force and material removal rate of AA 5083 aluminum alloy in CNC end milling using RSM. Arjun et al [19] studied the effect of input variables on surface roughness and material removal rate in milling of aluminum 7075 alloy by using Box-Behnken design in RSM. They developed mathematical models for output variables. DFA was used to optimize cutting parameters with the lowest surface roughness

EXPERIMENTAL PROCEDURES

Prediction of Surface Roughness using RSM

X: Internally Studentized Residuals Y

Optimization using DFA

CONCLUSION