THE EFFECT OF MACHINING PARAMETERS ON SURFACE ROUGHNESS USING RESPONSE SURFACE METHODOLOGY (RSM)

The effect of machining parameters on surface roughness using response surface methodology (RSM) was investigated. The data used for the work was obtained from the previous work titled ‘’effect of machining parameters on the surface roughness of medium carbon steel using lathe machine’’. The data was further expanded using the “Rand function” in Microsoft Excel. Five hundred (500) data points were generated from the original data using this function. These data points were used to perform the analyses in response surface methodology. The result revealed that the relative importance of feed rate was 45.91%, cutting speed was 28.94% and depth of cut was 25.15%. The quadratic model was selected to predict the mean surface roughness of the turning operation. The model, F- value of 31.34 implied that the model was significant. Values of “Prob > F” than 0.0500 indicated that model terms were significant, i.e. cutting speed, feed rate, and depth of cut were all significant effects on the mean surface roughness. The model was significant with a low probability value of 0.0001 and a satisfactory coefficient of determination, R2 = 0. 9658. The high coefficient of determination showed excellent correlation between the independent variables and the dependent variable (or response being the mean surface roughness). It was observed that the cutting speed and the depth of cut had a direct relationship with the mean surface roughness, while the feed rate had an indirect relationship on the mean surface roughness. From the results obtained from ANOVA, it was found that cutting speed had the most significant effect on the mean surface roughness, followed by depth of cut, and the feed rate. At lower values of feed, there was a gradual decrease in the values of surface roughness when the depth of cut was 0.35 mm. Finally the study revealed that with optimal values of cutting parameters of cutting speed, feed rate and depth of cut at 254.056 (rpm), 0.183419 (mm/rev) and 0.254583 (mm) respectively. Optimal minimum surface roughness was found to be 0.663487 (microns), and a desirability of 1.00 was obtained.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-22
DOI
https://doi.org/10.5281/zenodo.16925700
Primary Topic
Theoretical and Computational Physics
Type
article
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article

THE EFFECT OF MACHINING PARAMETERS ON SURFACE ROUGHNESS USING RESPONSE SURFACE METHODOLOGY (RSM)

Zenodo (CERN European Organization for Nuclear Research)
Theoretical and Computational Physics
article

THE EFFECT OF MACHINING PARAMETERS ON SURFACE ROUGHNESS USING RESPONSE SURFACE METHODOLOGY (RSM)

article en

Abstract

The effect of machining parameters on surface roughness using response surface methodology (RSM) was investigated. The data used for the work was obtained from the previous work titled ‘’effect of machining parameters on the surface roughness of medium carbon steel using lathe machine’’. The data was further expanded using the “Rand function” in Microsoft Excel. Five hundred (500) data points were generated from the original data using this function. These data points were used to perform the analyses in response surface methodology. The result revealed that the relative importance of feed rate was 45.91%, cutting speed was 28.94% and depth of cut was 25.15%. The quadratic model was selected to predict the mean surface roughness of the turning operation. The model, F- value of 31.34 implied that the model was significant. Values of “Prob > F” than 0.0500 indicated that model terms were significant, i.e. cutting speed, feed rate, and depth of cut were all significant effects on the mean surface roughness. The model was significant with a low probability value of 0.0001 and a satisfactory coefficient of determination, R2 = 0. 9658. The high coefficient of determination showed excellent correlation between the independent variables and the dependent variable (or response being the mean surface roughness). It was observed that the cutting speed and the depth of cut had a direct relationship with the mean surface roughness, while the feed rate had an indirect relationship on the mean surface roughness. From the results obtained from ANOVA, it was found that cutting speed had the most significant effect on the mean surface roughness, followed by depth of cut, and the feed rate. At lower values of feed, there was a gradual decrease in the values of surface roughness when the depth of cut was 0.35 mm. Finally the study revealed that with optimal values of cutting parameters of cutting speed, feed rate and depth of cut at 254.056 (rpm), 0.183419 (mm/rev) and 0.254583 (mm) respectively. Optimal minimum surface roughness was found to be 0.663487 (microns), and a desirability of 1.00 was obtained.

Zenodo (CERN European Organization for Nuclear Research)
University of Uyo (NG)
Openalex Percentile: Top 41%
Theoretical and Computational Physics
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