Details

Autor(en) / Beteiligte

• Liu, Xiaojian
• Xu, Jiarun
• Wang, Yang
• Qiu, Lemiao
• Zhang, Shuyou
• Tan, Jianrong
• He, Zhaolei

Titel

A systematic spatial-variably volumetric error model and machining optimization method based on continuous moving support variation of machine tool

Ist Teil von

• International journal of advanced manufacturing technology, 2023-11, Vol.129 (3-4), p.1189-1211

Ort / Verlag

London: Springer London

Erscheinungsjahr

2023

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• The real-time support variation of the machine tool is a source of systematic errors that cannot be ignored and has a great impact on the machining accuracy. The calculation and representation of moving support variation are important basis for improving machining accuracy. Different from the traditional data-based methods of static deformation measurement and compensation, this paper proposes a real-time continuous moving support deformation error model-based method to establish a systematic spatial-variably volumetric error model, which realizes the model decoupling of complex error sources of machine tools. The real-time deformation of moving support under multiple working conditions by FEM simulation is converted into the joint surface deformation of the moving system, and the translational and rotational position-dependent geometric errors (PDGE) are analyzed through the positional geometry of four sliders as joint surface, and the continuous moving variation errors along the single-axis and dual-axis motion space is generated. Further, based on the homogeneous transformation theory, the multi-axis 6-DOF PDGE are fused to construct a spatial-variably volumetric error model. In addition, this paper adopts a machining optimization method, which can efficiently identify the optimal machining space for the machine tool according to the machining features of the workpiece and the spatial-variably volumetric error model. In the case study, the proposed method is applied to a horizontal machining center, the detailed characterization of the spatial-variably error is given, and the optimal machining space is identified for different sample workpieces, which proves that it can effectively improve the machining accuracy of the machine tool.