To meet the growing demand for higher machining accuracy, it is crucial to improve and sustain the accuracy of five-axis machine tools. Nonetheless, the accuracy of these machine tools is significantly affected by geometric errors and degrades over time. Traditional interferometry-based techniques are commonly used to identify these errors, but on-machine measurement (OMM) has emerged as a viable and increasingly available alternative method. An iterative geometric error identification method to identify position-independent geometric errors (PIGEs) and position-dependent geometric errors (PDGEs) of rotary axes simultaneously is proposed. Firstly, the kinematic error model of the five-axis machine tool is established and geometric errors are defined. Subsequently, the PIGEs and PDGEs of the rotary axes are identified simultaneously on the basis of the preliminary identifications. Additionally, uncertainty analysis of error identification is executed to assess the reliability of the proposed method. Identification experiments using OMM are carried out. The experiment result demonstrates the effectiveness of the proposed method. Performing periodic verification on machine tool accuracy, as outlined in ISO 230-2, allows for continual monitoring and prompt detection of any degradation in accuracy. The proposed OMM-based identification method is more efficient for performing periodic verification of machine tool accuracy.
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