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Abstract

This research investigates the intricate relationship between cutting parameterscutting speed, feed rate, and depth of cut and surface roughness in machining processes. Surface roughness is a key determinant of machined surface quality, and optimizing cutting parameters is crucial for achieving superior finishes. Employing advanced visualization techniques, including contour plots and 3D surface profiles, the study offers a comprehensive exploration of surface topography dynamics. Statistical analyses and regression modeling enhance the quantitative understanding of how cutting parameters interact to shape surface roughness. The research affirms the significant influence of cutting speed, feed rate, and depth of cut, providing practical insights for industries seeking to balance efficiency and quality in manufacturing. This study contributes not only to academic knowledge but also directly informs manufacturing practices. Practical guidelines derived from the analysis offer actionable insights, and regression models provide predictive capabilities for optimizing surface finishes under specific machining conditions. The integration of theoretical insights and practical implications positions this research as a valuable resource for researchers and practitioners in precision machining.

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85

References

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