Title: Optimisation of forging parameters of 35C8 steel using grey relational analysis

Authors: Md Israr Equbal; Azhar Equbal; Md Asif Equbal; R. Pranav

Addresses: Department of Mechanical Engineering, J.B. Institute of Engineering and Technology, Moinabad, Hyderabad – 500075, India ' Department of Mechanical Engineering, R.T.C. Institute of Technology, Ormanjhi, Ranchi – 835219, India ' Department of Mechanical Engineering, Cambridge Institute of Technology, Tatisilwai, Ranchi – 835103, India ' Department of Mechanical Engineering, Aurora's Technological and Research Institute, Uppal, Hyderabad – 500098, India

Abstract: In metal forging operations desired microstructures with optimum mechanical properties of the forged part is really a tedious job. The microstructures, as well as the mechanical properties, depending on many process variables either directly or indirectly. This study involves experimental investigation of optimal set of process parameters such as forging temperature, percentage deformation and cooling rate during hot forging process to optimise the mechanical properties like tensile strength and impact strength of commercial medium carbon forging steel. All forgings have been completed in between flat dies of 150 tonne hydraulic press. To reduce the number of experimental runs Taguchi's orthogonal array was used. Analysis of variance is employed to determine significant parameters. Based on the experiments conducted, analysis has been carried out using the grey relational analysis, a Taguchi method. The confirmation experiments were carried out to validate the optimal results. The mechanical properties obtained have been correlated with microstructures using a high magnification optical microscope.

Keywords: metal forging; microstructure; orthogonal array; ANOVA; analysis of variance; grey relational analysis.

DOI: 10.1504/IJMMP.2018.096144

International Journal of Microstructure and Materials Properties, 2018 Vol.13 No.3/4, pp.198 - 212

Received: 21 Nov 2017
Accepted: 29 May 2018
Published online: 13 Nov 2018 *

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