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Reconfigurable Data Driven Virtual Machine Tool: Geometric Error Modeling and Evaluation

Published

Author(s)

Ronnie R. Fesperman Jr., Shawn P. Moylan, Gregory W. Vogl, M A. Donmez

Abstract

Standards communities are actively working to establish robust machining and measurement tests used to evaluate the machining performance of 5-axis machining centers through the direct and indirect measurement of the simultaneous motions of all five axes. However, the compound effect of the individual geometric errors and servo mismatch errors makes the analysis of the measurement results complicated and the identification and separation of the individual error contributor(s) difficult. To better understand the effect of the individual errors on the measurement results, we developed a multi-configuration five-axis Data Driven Virtual Machine Tool (DDVMT) error simulator. The DDVMT is a generalized model that incorporates machine tool information models, geometric error models, controller models, and standardized machine tool metrology test methods and analyses into one modeling scheme. The present paper describes the Data Driven Virtual Machine Tool and reports results that demonstrate its ability to simulate the effects of geometric errors on multi-axis measurements.
Citation
CIRP Journal of Manufacturing Science and Technology
Volume
10

Keywords

Five-axis machine tools, Data driven, Virtual machine tool, Information modeling, Geometric error modeling, Standards

Citation

Fesperman, R. , Moylan, S. , Vogl, G. and Donmez, M. (2015), Reconfigurable Data Driven Virtual Machine Tool: Geometric Error Modeling and Evaluation, CIRP Journal of Manufacturing Science and Technology, [online], https://doi.org/10.1016/j.cirpj.2015.03.001 (Accessed February 22, 2024)
Created August 31, 2015, Updated November 10, 2018