Statistical analysis of the theoretical geometric-kinematic surface roughness model at turning

Manufacturing methods can produce precision machined parts where surface roughness is an important performance characteristic, affecting fatigue strength, corrosion resistance, and aesthetics. Achieving ideal surface roughness is complex, influenced by tool-material interactions and machine conditions. Predicting surface roughness has high importance in machine design and manufacturing process planning. Key approaches include: machining theory (analytical models using cutting parameters), data analysis (empirical/statistical methods), designed experiments, AI, and image processing. The article presents a geometric-kinematic surface roughness model, and based on it the standard surface roughness parameters are determined. The arc based profile model is used, and the model makes possible to use a statistical analysis based improvement method in order to increase the accuracy of the prediction. The theoretical model, the process of the calculation and the regression analysis of the model is presented.