Comparative Study to Optimize Surface Roughness of the Titanium Alloy Ti-6Al-4V by Applying Taguchi, RSM and TLBO Methods

Abstract

Titanium alloys are used in aeronautics and the shipbuilding industry for their good intrinsic properties, namely low density (40% less than steel), very good mechanical properties and resistance to corrosion. The purpose of this study is to optimize the cutting conditions during the turning of Ti-6Al-4V titanium alloy with Minimum of Quantity of Lubrication (MQL) conditions leading to minimize the surface roughness (Ra). The tests were carried out according to a Taguchi L18 design plan by varying four input factors namely: the cutting speed, the feed rate, the depth of cut and the cutting tool material (coated carbide with (PVD) (GC1125) and uncoated carbide (H13A)). Analysis of variance (ANOVA) was used to found the contribution of each factor and to determine which parameters had a significant influence on the surface roughness. The treatment of the results made it possible to propose a mathematical model, which allows predicting Ra. In addition, Taguchi Signal/Noise (S/N) analysis was used in order to optimize the cutting conditions permitting to minimize Ra. The Desirability Function (DF) was also determined. In addition, the obtained results were compared to the one determined using Response Surface Methodology (RSM) and Teaching and Learning Based Optimization (TLBO). It is important to note that the TLBO method gave a very satisfactory result.