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All Journal Jurnal Vokasi Mekanika
Rio Evandi
Universitas Tidar
Education Mechanical Engineering

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Data-Driven Analysis of Machining Parameters Affecting Surface Roughness (Ra) in CNC Turning of Al6061 Using OLS Method Dimas Ardiansyah Halim; Arbey, S; Rio Evandi; Tosa Susilo; Joko Suparno
Jurnal Vokasi Mekanika (VoMek) Vol 8 No 2 (2026): Jurnal Vokasi Mekanika
Publisher : Unversitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/e9fjmj14

Abstract

This study aims to analyze the effect of machining parameters on surface roughness (Ra) in the CNC turning process of Aluminum 6061 using the Ordinary Least Squares (OLS) approach. The investigated parameters include cutting speed (v), feed rate (f), nose radius (r), and spindle speed (n). The experimental design was developed using a Central Composite Design (CCD) with five coded levels (+2, +1, 0, ?1, ?2). The machining process was carried out on a CNC GSK 980TDi lathe using CCMT inserts with nose radii of 0.2 mm, 0.4 mm, and 0.8 mm, while the surface roughness was measured using a Mahr Marsurf M300 tester with an accuracy of 0.076 µm. Experimental data were analyzed using the OLS method to determine the most dominant parameters affecting Ra. The results show a coefficient of determination (R²) of 0.932 and an adjusted R² of 0.868, indicating that the regression model provides an excellent level of fit. The nose radius (r) and spindle speed (n) were found to be the most significant factors influencing surface roughness, exhibiting opposite effects. This data-driven approach demonstrates the effectiveness of the OLS method in identifying critical machining parameters in CNC turning processes.
Co-Authors Arbey, S Dimas Ardiansyah Halim Joko Suparno Tosa Susilo