A model-based approach for monitoring of ball nose milling by force sensing

Abstract

Ball nose milling is most commonly used in computer-controlled sculpture surface machining using computer numerical control (CNC) machines. Tool condition monitoring (TCM) for the ball nose milling by CNC machines will significantly improve machining efficiency, minimize inaccuracy, minimize machine down time, and maximize tool life utilization. Central to TCM is tool wear monitoring, and wear monitoring of ball nose milling poses new challenges compared with the conventional machining. This paper presents a model-based approach to estimate and track the tool wear profile along the cutting edge for ball nose milling based on the cutting force against it. The model-based approach uses a geometric model and a cutting force model to characterize the ball nose milling process and estimate the tool wear profile. The geometric model is used to determine the geometric features, such as the chip load along the cutting edge, and friction length for given tool path direction and the cutting parameters. The mechanistic cutting force model is developed using the chip load about the cutter rotation axis and the cutting coefficients. The chip load is derived from the geometric model, while the cutting coefficients are determined using the chip load and experimentally measured cutting force when machining on an inclined plane. To verify the proposed tool wear estimation models, experiments were conducted on a hemispherical work piece with different sequence of cutter path directions to simulate variable contact between the ball nose cutter and the work piece surface as encountered in sculptured machining. The tool wear profile was measured and compared with the estimated tool wear profiles from the models. Two variations of the model-based approaches are also compared with the proposed approach for tool wear profile estimation and the best and robust match has been observed for the proposed approach.