PROBABILISTIC PREDICTION OF BURR PATTERNS OF 1045 CARBON STEEL IN FACE MILLING

Abstract

Face milling burrs in ductile materials such as 1045 carbon steel exhibit three distinct burr patterns: uniform, wavy, and secondary burrs. It is found that the three burr patterns are dependent on the in-plane exit angle, undeformed chip ratio, and undeformed chip area at the exit stage of cut. Empirical equations, representing the burr transition curves from the uniform to wavy burr and wavy to secondary burr, are found. Based on the empirical relationships, a probabilistic model, in which the operational Bayesian modeling approach is adopted to include the empirical equations, is derived for burr prediction.