Application of GRA method for multi-objective optimization of roller burnishing process parameters using a carbide tool on high carbon steel (AISI-1040)

Abstract

Purpose The purpose of this paper is to analyze and optimize the roller burnishing process parameters using the design of experiments and grey relational analysis (GRA). Design/methodology/approach In this experimental work, the carbide burnishing tool has been selected for the machining of AISI-1040 high carbon steel to get better product quality and satisfactory machining characteristics. The material surface condition while machining, burnishing tool speed, feed rate, depth of penetration and No. of passes have been selected as process constraints to conduct experimental trials. Findings The surface roughness (SR) and surface hardness were considered as output responses. The experimental outcomes optimized by multi-parametric optimization showed considerable improvement in the process. The roller speed and number of passes are the most significant parameters for surface hardness, whereas the surface condition and roller penetration depth have the most significance on SR. Research limitations/implications The GRA method shows the 0.03376 improvement in grey relational grade between the experimental values and the predicted values. Practical implications The experimental outcomes optimized by multi-parametric optimization showed the considerable improvement in the process and will facilitate steel industries to enhance and improve productivity while burnishing high carbon steel (AISI-1040). Originality/value This research represents valid work, and the authors have no conflict of interests.