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A machining accuracy improvement approach for a horizontal machining center based on analysis of geometric error characteristics.

Authors :
Niu, Peng
Cheng, Qiang
Liu, Zhifeng
Chu, Hongyan
Source :
International Journal of Advanced Manufacturing Technology. Jan2021, Vol. 112 Issue 9/10, p2873-2887. 15p.
Publication Year :
2021

Abstract

In the actual production, it is expected to find several sensitivity geometric errors which have great influence on machining accuracy, so as to provide references for the manufacturing, assembly, and other links of the machine tool, and fundamentally improve the working performance. To study this problem, a novel global sensitivity analysis (GSA) method is proposed. Based on the MBS theory, the spatial error model is established to analyze the local influence of geometric error on machining accuracy. An improved second-order partial correlation coefficient based on the Pearson product moment is proposed to analyze the correlation between geometric errors. In addition, the error parameters will change greatly in the stroke of the moving parts. However, the rapid fluctuation of geometric error value will have a dynamic impact on the machining accuracy of machine tools, which is rarely noticed in the previous sensitivity analysis. This change is defined as the fluctuation of error. The high fitting degree function of error-displacement is obtained by using the high order Fourier series and sine series. Then, the fluctuation of the error in the machining stroke is analyzed by using the derivative of the function to the displacement. Through geometric error characteristics (including the local influence, correlation, and fluctuation) are studied comprehensively, the GSA of error is carried out. Finally, taking a machining center as an example and combining the sensitivity analysis results, the improvement measures are proposed to verify the correctness of the method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02683768
Volume :
112
Issue :
9/10
Database :
Academic Search Index
Journal :
International Journal of Advanced Manufacturing Technology
Publication Type :
Academic Journal
Accession number :
148233031
Full Text :
https://doi.org/10.1007/s00170-020-06565-3