3.8 Proceedings Paper

Experimental investigation of process parameters on surface roughness and dimensional accuracy in hard turning of EN24 steel

Journal

MATERIALS TODAY-PROCEEDINGS
Volume 57, Issue -, Pages 674-680

Publisher

ELSEVIER
DOI: 10.1016/j.matpr.2022.02.104

Keywords

Hard turning; EN24 steel; Surface roughness; Dimensional accuracy; Taguchi; ANOVA

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This study focuses on the surface roughness and dimensional accuracy of EN24 steel in hard turning. Experimental findings, using the Taguchi method and analysis of variance, determined the optimal process parameters. The results showed that spindle speed had the greatest impact on component surface roughness, followed by insert nose radius, while feed rate and cutting depth had a lesser impact. Cutting depth had a significant influence on dimensional accuracy, followed by spindle speed and nose radius.
Hard turning is the process of cutting hardened components with hardness ranging from 45 to 70 HRC within the 2-mm range. Hard turning differs from traditional turning in the sense that during hard turning it is very difficult to achieve surface finish and dimensional accuracy as compared to traditional turning. The present work focuses on the investigation of surface roughness and dimensional accuracy of EN24 steel in hard turning. Cutting tool used in this experimentation is CBN. Speed of spindle, rate of feed, nose radius, and cut depth are all variables in the process. The process is carried out by CNC lathe machine. Surface roughness values are measured by surface roughness meter and dimensional accuracy is measured using precision dial gauge. Taguchi method is used to conduct a set of experiments using design of experiments (DOE) with L9 orthogonal array. Using a statistical technique, the best values for process parameters such as surface roughness and dimension accuracy are determined based on experimental findings. The ideal process parameters on response, such as surface roughness and dimensional accuracy, were determined using analysis of variance (ANOVA). The Signal to Noise (S/N) Ratio was utilised to determine the ideal process parameter levels. The results show that spindle speed has the greatest impact on component surface roughness, followed by insert nose radius, while feed rate and cutting depth have a lesser impact when compared to the other factors. Furthermore cutting depth has significant influence on Dimensional accuracy of parts followed by spindle speed and nose radius, where as feed rate has little influence compared to others parameters.Copyright (c) 2022 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Third International Conference on Aspects of Materials Science and Engineering.

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