Adaptive Thermal Error Compensation Model of a Horizontal Machining Centre

Abstract The state-of-the-art method to reduce CNC machine tool thermal errors is real-time error compensation based on the estimation models. However, it difficult establish a model with good versatility, high accuracy, and strong robustness due various manufacturing conditions thermally varying surrounding environment. It causes that behaviour of tools nonlinear in real time. Consequently, pre-trained non-adaptive may not be accurate robust enough for long-term application. presented research shows systematic adaptation technique update horizontal machining centre under conditions, which differ from calibration test. System identification theory applied build dynamic Linear parametric models autoregressive external input (ARX) present an established method, its modelling calculation speed are suitable applications. Additionally, process-intermittent probing integrated into management software monitor compensate at point (TCP) time using C#/C++ programming language. results show prediction accuracy measured as peak-to-peak values normalized root mean squared improved by up 33% 51%, respectively, when adaptive applied.