Optimization of Process Parameters in Magnetic Surface Grinding of EN8 Steel

The realization of precise surface characteristics and dimensional tolerances in engineering components critically influenced by the operational effectiveness of surface grinding procedures. The attainment of precise surface finish is vital for EN8 steel. A medium carbon alloy steels generally used in manufacturing and automotive components, to ensure superior operational performance and longevity. This work focuses on optimizing the process parameters in magnetic surface grinding machine to improve the surface integrity and reduce the non uniform material removal. The grinding wheel speed, feed, depth of cut and magnetic field strength are the main process variables taken into account. To methodically examine the impact of these parameters on surface roughness and material removal rate, experiments were carried out using the Taguchi method. The most significant factors affecting grinding performance were identified using the signal to noise(S/N) ratio and analysis variance (ANOVA). The results indicate that magnetic assistance greatly enhances grinding efficiency and surface quality by reducing friction and heat related defects. Optimal settings are proposed to secure superior surface characteristics and enhanced output rates. The work offers significant knowledge regarding the effectiveness of magnetic aid in precision machining of ferromagnetic materials like EN8 steel.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-30
DOI
https://doi.org/10.5281/zenodo.19206347
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization of Process Parameters in Magnetic Surface Grinding of EN8 Steel

Ravi Kanth N, Malleswara Rao M
Zenodo (CERN European Organization for Nuclear Research)
Advanced machining processes and optimization
article

Optimization of Process Parameters in Magnetic Surface Grinding of EN8 Steel

Ravi Kanth N, Malleswara Rao M
article en

Abstract

The realization of precise surface characteristics and dimensional tolerances in engineering components critically influenced by the operational effectiveness of surface grinding procedures. The attainment of precise surface finish is vital for EN8 steel. A medium carbon alloy steels generally used in manufacturing and automotive components, to ensure superior operational performance and longevity. This work focuses on optimizing the process parameters in magnetic surface grinding machine to improve the surface integrity and reduce the non uniform material removal. The grinding wheel speed, feed, depth of cut and magnetic field strength are the main process variables taken into account. To methodically examine the impact of these parameters on surface roughness and material removal rate, experiments were carried out using the Taguchi method. The most significant factors affecting grinding performance were identified using the signal to noise(S/N) ratio and analysis variance (ANOVA). The results indicate that magnetic assistance greatly enhances grinding efficiency and surface quality by reducing friction and heat related defects. Optimal settings are proposed to secure superior surface characteristics and enhanced output rates. The work offers significant knowledge regarding the effectiveness of magnetic aid in precision machining of ferromagnetic materials like EN8 steel.

Zenodo (CERN European Organization for Nuclear Research)
Government of Andhra Pradesh (IN)
Openalex Percentile: Top 11%
Advanced machining processes and optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.