Optimization of Process Parameters in CNC End Milling of Mild Steel Using Response Surface Methodology

This study investigates and optimizes the machining parameters of the CNC end milling process applied to mild steel workpieces, with a focus on surface roughness measurements. Traditional approaches typically assess surface roughness post-machining, but this research employs Response Surface Methodology (RSM) to analyze the impact of critical milling parameters—spindle speed (N), depth of cut (d), and feed rate (f)—on surface finish. The experimental work was conducted using Minitab 18 software, and response optimization techniques were utilized through Regression Analysis (RA) to determine the optimal process parameters. The optimized parameters identified include a spindle speed of 2000 m/min, a feed rate of 700 mm/pass, and a depth of cut of 0.1 mm, which achieved a minimum surface roughness of 1.64256 μm. The proposed model demonstrated an accuracy of over 80% in fitting the investigated values, indicating its effectiveness in identifying optimal conditions and enhancing milling process efficiency.

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Publication Details

Published
2024-12-21
DOI
https://doi.org/10.46254/ba07.20240048
Citations
1
Primary Topic
Advanced machining processes and optimization
Type
article
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article

Optimization of Process Parameters in CNC End Milling of Mild Steel Using Response Surface Methodology

Sajjad Muhammad, Rakesh Roy, Mst. Jeba Shazida, Md Masum Billah et al.
1 citations
Advanced machining processes and optimization
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article

Optimization of Process Parameters in CNC End Milling of Mild Steel Using Response Surface Methodology

Sajjad Muhammad, Rakesh Roy, Mst. Jeba Shazida, Md Masum Billah, Mohaiminul Islam, Sarojit Kumar Biswas, Raton Kumar Mollik
article en
1 citations

Abstract

This study investigates and optimizes the machining parameters of the CNC end milling process applied to mild steel workpieces, with a focus on surface roughness measurements. Traditional approaches typically assess surface roughness post-machining, but this research employs Response Surface Methodology (RSM) to analyze the impact of critical milling parameters—spindle speed (N), depth of cut (d), and feed rate (f)—on surface finish. The experimental work was conducted using Minitab 18 software, and response optimization techniques were utilized through Regression Analysis (RA) to determine the optimal process parameters. The optimized parameters identified include a spindle speed of 2000 m/min, a feed rate of 700 mm/pass, and a depth of cut of 0.1 mm, which achieved a minimum surface roughness of 1.64256 μm. The proposed model demonstrated an accuracy of over 80% in fitting the investigated values, indicating its effectiveness in identifying optimal conditions and enhancing milling process efficiency.

Openalex Percentile: Top 48%
Advanced machining processes and optimization
0.21
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