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A Novel Error Compensation Method for Multistage Machining Processes Based on Differential Motion Vector Sets of Multiple Contour Points.

Authors :
Mengrui Zhu
Guangyan Ge
Xiaobing Feng
Zhengchun Du
Jianguo Yang
Source :
Journal of Manufacturing Science & Engineering. Jun2021, Vol. 143 Issue 6, p1-14. 14p.
Publication Year :
2021

Abstract

Modeling the variation propagation based on the stream of variation (SoV) methodology for multistage machining processes (MMPs) has been investigated intensively in the past two decades; however, little research is conducted on the variation reduction and the existing work fails to be applied to irregular features caused by the machining-induced variation varying with the positions of the contour points on the machined surface. This paper proposes a novel error compensation method for MMPs by modifying the tool path to reduce variation for general features. The method based on differential motion vector (DMV) sets of multiple contour points is presented to represent the deviation of the irregular feature. Then, the conventional stream of variation (SoV) model is further extended to more accurately describe variation propagation for irregular features considering the actual datum-induced variations and the varying machining-induced variations, especially the deformation errors for the low stiffness workpiece. Based on the extended SoV model and error equivalence mechanism, the datum error and fixture error are transformed to the equivalent tool path error. Then, the original tool path is modified through shifting the machine zero points of machine tools with no need for changing the original G code and workpiece setup. A real cutting experiment validates the effectiveness of the proposed error compensation method for MMPs with an average precision improvement of over 60%. The application of the extended SoV model significantly contributes to compensating more complex error sources for MMPs, such as the clamp force, the internal residual stress, etc. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10871357
Volume :
143
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Manufacturing Science & Engineering
Publication Type :
Academic Journal
Accession number :
150221093
Full Text :
https://doi.org/10.1115/1.4049036