Multi-Objective Optimization of Material Removal Rate and Surface Roughness in Dry Turning of Aluminium Alloy AA7075 Using Taguchi-Utility Method

Abstract

In the present work, Taguchi techniques are employed to find out the optimal combination of
cutting parameters in dry turning of Aluminium alloy AA7075 using a tungsten carbide tool.
The experiments are planned as per the Taguchi’s standard L9 (3^3) Orthogonal Array. Cutting
speed, feed and depth of cut are selected as the three controllable variables at three different
levels, whereas Material Removal Rate (MRR) and Surface Roughness (Ra) are considered
as the experimental output characteristics. Single objective Taguchi method and
Taguchi based Utility methods are employed for the optimization of individual and multiresponses
respectively. From the single objective Taguchi method, the optimal setting of the
cutting parameters is found at N3-f3-d3 (2000 RPM, 0.4 mm/rev, 1 mm) for Material Removal
Rate and at N1-f1-d2 (1000 RPM, 0.2 mm/rev, 0.75 mm) for Surface Roughness. The
ANOVA and F-tests are used to find the significance of the cutting parameters on the responses
and from the results it is found that the depth of cut and feed are the more significant
parameters in effecting the MRR and Ra respectively. The results of multi-response optimization
based on utility analysis show that high values of cutting speed (2000 RPM), depth of cut
(1 mm) and a low value of feed (0.2 mm/rev) are required to achieve a high material removal
rate and low surface roughness simultaneously. The feed is found to be the high significant
parameter in affecting the multi-responses.