A Novel Approach of Turning on Titanium(Ti-6AL-4V) Alloy using NFGMT Coupled with GRA, PCA, and RSM

Sivakoteswararao Katta*, Mihai Dupac**, Baojian Guo***
*Research Scholar, Department of Mechanical Engineering, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India.
**Associate Professor, Department of Mechanical Engineering, RVR&JC College of Engineering, Guntur, Andhra Pradesh, India.
***Associate Professor, Department of Mechanical Engineering, Bapatla Engineering College, Bapatla, Andhra Pradesh, India.
Periodicity:November - January'2019
DOI : https://doi.org/10.26634/jme.9.1.14813

Abstract

The present work attempted to find the impact of proces parameters on turning titanium grade 5 alloys and accurate optimization model for responses, such as cutting force, cutting time, and temperature using Principal Component Analysis (PCA), Gray Relational Analysis (GRA), and (RSM) Response Surface Methodology optimization techniques. Graphene Nanoparticles are used to mix with the vegetable oil based (Soya Bean) cutting fluid. The experiment has been done by using machining parameters, such as feed rate, cutting speed, depth of cut, and an analysis has been made to evaluate the machining parameters for cutting force, cutting time, and temperature based on the actual series of experiments with uncoated carbide tool. The outcomes state that the depth of cut and speed has a greater influence on the values of cutting force and temperature as compared to feed. The predicted results are identical to the experimental values. Since this research is multi-objective, these developed models using RSM and PCA can be used for the evaluation of cutting force, temperature, and cutting time as well.

Keywords

Nanofluid-Based Green Machining Technique (NFGMT), Response Surface Methodology (RSM), Principal Component Analysis (PCA), Machining Parameters

How to Cite this Article?

Katta, S., Chaitanya, G., and Shankar, B. R. (2019). A Novel Approach of Turning on Titanium (Ti-6AL-4V) Alloy using NFGMT Coupled with GRA PCA and RSM. i-manager’s Journal on Mechanical Engineering, 9(1), 13-21. https://doi.org/10.26634/jme.9.1.14813

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