Probabilistic Analysis of Surface Integrity in CNC Turning: Influence of Thermal Conductivity and Hardness on Roughness and Waviness Distributions

This study presents a probabilistic analysis of how thermal conductivity and hardness affect surface integrity in CNC turning, focusing on five engineering materials: Aluminum Alloy 6061, Brass C26000, Bronze C51000, Carbon Steel 1020 Annealed, and Stainless Steel 304 Annealed. Surface roughness and waviness parameters were measured across five zones per material under controlled conditions. Results revealed a strong inverse correlation between thermal conductivity and surface irregularities. Aluminum Alloy 6061 (167 W/m·K, 95 HBW) exhibited the best surface finish (Ra_avg ≈ 1.7664 µm; Wa_avg ≈ 0.8242 µm), while Carbon Steel 1020 Annealed (51 W/m·K, 170 HBW) demonstrated the poorest finish (Ra_avg ≈ 4.0780 µm; Wa_avg ≈ 3.8384 µm). Intermediate materials followed consistent trends: Brass C26000 (Ra_avg ≈ 2.5398 µm; Wa_avg ≈ 1.5364 µm), Bronze C51000 (Ra_avg ≈ 1.8862 µm; Wa_avg ≈ 0.9299 µm), and Stainless Steel 304 Annealed (Ra_avg ≈ 0.9031 µm; Wa_avg ≈ 0.5914 µm). High thermal conductivity materials exhibited narrower parameter distributions (σ_Ra ≤ 0.40 µm), while harder materials showed increased variability (σ_Ra ≥ 0.60 µm). Probabilistic models, validated with high confidence (R2 > 0.95), offer predictive insights for optimizing machining strategies. These findings support material-specific process adjustments to enhance surface quality, tool life, and functional reliability in aerospace, automotive, and biomedical applications.