Open AccessInfluence of Cutting Parameter and Multi-Objective Optimization on Turning Titanium Alloy
Author(s) -
Juri Saedon,
Muhamad Fauzi Othman,
Mohd Suhairil Meon,
Nik Hisyamudin Muhd Nor,
Hazran Husain,
S. Shawal
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1092/1/012060
Subject(s) - titanium alloy , surface roughness , machining , materials science , factorial experiment , response surface methodology , titanium , surface finish , metallurgy , tool wear , alloy , design of experiments , work (physics) , mechanical engineering , composite material , computer science , mathematics , engineering , machine learning , statistics
Turning is one of the conventional material removal processes and it is essential in today’s manufacturing industry. Nowadays, titanium alloys are favorable and widely used material due to its superior material properties. However, despite having superior material properties, titanium alloys are hard to machine and will result in shortened tool life. Hence it is important to determine the suitable turning parameter to prolong tool life with best surface roughness. This work focused on investigating the influence of machining parameters in machining titanium alloy under dry cutting condition. The influence of three machining parameters namely feeds rate, cutting speed and depth of cut are investigated using a full factorial design. Surface roughness and tool wear were the responses variables. Analysis of variance was utilized in the analysis to determine their contribution ratio and interaction on each response. The experimental results showed that the feed rate was identified as the most influential factor on surface roughness and tool wear at 54% and 33% contribution ratio respectively. Further multi-response objective optimization was adopted through the desirability function analysis method. For the titanium turning operation, the minimal surface roughness and tool wear were significantly obtained through the specified machining parameters at cutting speed of 44 m/min, feed rate of 0.05 mm/rev and depth of cut of 0.5 mm. The results showed that the single objective response successfully converted into multi-objective optimization through the desirability function analysis method.