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Prediction of Process Parameters in Turning of Titanium Alloys using Response Surface Methodology
Author(s) -
Siva koteswararao. Katta et al. Siva koteswararao. Katta et al.
Publication year - 2018
Publication title -
international journal of mechanical and production engineering research and development
Language(s) - English
Resource type - Journals
eISSN - 2249-6890
pISSN - 2249-8001
DOI - 10.24247/ijmperdfeb201860
Subject(s) - materials science , process (computing) , titanium , response surface methodology , titanium alloy , metallurgy , computer science , process engineering , engineering , machine learning , alloy , operating system
Manufacturing of titanium products is difficult bec ause of its machining. The demand for titanium prod ucts is increasing rapidly in the applications of surgical components, nuclear reactors, boilers, human in-pla nts, automobile industries. Because of inherent properties like high heat resistant, high strength, high chemical react ion with other metals, machining of titanium alloys is always a ch allenge for manufacturers by using innovative metho d logy and machining techniques to improve productivity of tit anium components. The present study is carried out n three different titanium alloys which are used for machining titani um alloys (Ti-Grade2, Ti-6al-4v, Ti-6al-4vELI) with u ncoated carbide tools used. Total experiments are performed under d ry environment for reducing the cost and optimizing the parameters of surface roughness and cutting force to predict t he value design of expert software, ANOVA used. Machin ing of titanium alloys with uncoated carbide inserts in dry environment is not suggestible, machining of grade – 5(TI-6AL-4V) with uncoated carbide inserts in dry environment is good and it will deliver better surface roughness an d cutting force compared to other two titanium alloys. Optimal cutti ng conditions are speed171.59 m/min, feed 0.12 mm/r ev, depth of cut 0.70mm titanium (TI-6AL-4V) grade 5, surface roughne ss 0.647μm, and cutting force 119.182N.

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