Prediction and evaluation of surface roughness on ceramic cutting insert during bone cutting

Surface roughness is a critical parameter to characterize surface quality in modern manufacturing industry. Developing a comprehensive theoretical model that can effectively represent the real machined surface is remain challenging due to the complexity of the machining process and the presence of uncontrollable factors such as tool wear. This work proposes a mathematical model for predicting surface roughness in milling of artificial bone using ceramic cutting insert of ZrO2. This study incorporates with two cutting parameters of speed rate (300 and 500 mm/min) and spindle speed (900 and 1000 rpm) to form empirical model. The results demonstrate that the pro-posed provides reliable predictions though the calculated error percentages varied from 22.4% to 33.3%. This discrepancy suggests that further refinements are necessary to enhance the prediction models. The findings provide important insights into the prediction and analysis of surface roughness in ceramic insert for bone cutting, hence promoting improvements in machining efficiency and surface quality evaluation. The novelty of this study is the developments of regression method to predict surface roughness using a customized ZrO2 ceramic cutting insert in bone cutting procedures.