When machining high precision mechanical parts, self-excited chatter vibrations must be absolutely avoided since they cause
unacceptable surface finish and dimensional errors. Such unstable vibrational phenomena typically arise when the overall
machining system stiffness is relatively low, as in the case of internal turning operations performed with slender boring bars. In
general, it is not easy to determine stable tooling system configurations for a given machining operation, since data available in
literature are often incomplete or inaccurate. In this paper, a new probabilistic algorithm for a robust analysis of stability in
internal turning is presented. In this approach, model parameters are considered as random variables, and robust analysis of
stability is carried out in order to estimate system’s probability of instability for a given boring bar geometry and material, tool
geometry, workpiece material and cutting parameters. By so doing, robustly stable tooling system configurations and cutting
conditions may be identified in the preliminary production planning phase. The proposed approach was experimentally validated
by considering different boring bar geometries and materials (including special boring bars made of high-damping carbide), tool
geometries, workpiece materials and cutting conditions. For each machining system configuration, the developed approach was
capable of successfully estimating the maximum ratio between boring bar overhang L and bar diameter D which assures process
stability for most cutting parameters combinations.
