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A novel sensitivity analysis of translational axis operation considering key component tolerances

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Abstract

At present, it is difficult to predict the operation accuracy of machine tools in the preliminary design stage. How to quantitatively reflect the contribution of tolerance on the position error of machine tool has a significant guidance for machine tool design stage. Thus, this paper presents a sensitivity analysis method based on components tolerance, which can clearly give the machine tool designer key the tolerances. Firstly, taking the translational axis as the research object, the operation accuracy model of Y-axis is established based on the homogeneous transform matrix (HTM) and multi-body system (MBS) theory. Meanwhile, the relationship between tolerances and geometric errors has been mapped by the Fourier expansion and the model of parameters have been identified by self-design simulation. As a basis, the tolerance sensitivity analysis (TSA) method based on the single-factor partial derivation is constructed to acquire the key tolerance parameters. Finally, the result of the experiment shows that the assembly tolerance of the Y-Z plane of the base, the manufacturing tolerance of the lead screw and the assembly tolerance of the X-Y plane of the carriage contribute a great deal to the position error, which needs to be strictly controlled in the future design to improve the accuracy of the machine tool.

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Funding

This work is financially supported by the National Natural Science Foundation of China (grant No. 51775010 and 51705011 ), the National Science and Technology Major Project of China (grant No. 2019ZX040 06001).

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Jinwei Fan and Peitong Wang provided ideas for this study, wrote codes and manuscripts. Xingfei Ren were responsible for the experiment in this study. All authors contributed to this study.

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Correspondence to Peitong Wang.

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Fan, J., Wang, P. & Ren, X. A novel sensitivity analysis of translational axis operation considering key component tolerances. Int J Adv Manuf Technol 118, 1255–1268 (2022). https://doi.org/10.1007/s00170-021-07932-4

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  • DOI: https://doi.org/10.1007/s00170-021-07932-4

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