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Comparative Statistical Analysis of Test Parts Manufactured in Production Environments

Published

Author(s)

David E. Gilsinn, Alice V. Ling

Abstract

Estimating error uncertainties arising in parts produced on machine tools in production machine shops is not a well understood process. The current study details a process of estimating these error uncertainties. A part with significant features was defined and a vertical turning center was selected in a production shop to make multiple copies of the part. Machine tool error components were measured using a laser ball bar instrument. Twenty-one copies of the part were produced and measured on a coordinate measuring machine. A machine tool error model based on the measurements of the vertical turning center machine tool errors was developed. Uncertainty estimates of the errors in the working volume were calculated. From coordinate measuring machine data error uncertainties at points on the part were developed. Distances between hole centers were computed and uncertainty estimates of these lengths generated. Many of the hole centers were designed to fall along orthogonal lines. Uncertainty estimates were computed of the orthogonality of these lines. All of these estimated uncertainties were compared against uncertainties computed from the measured parts. The mainconclusion of the work is that the Law of Propagation of Uncertainties can be used to estimate machining uncertainties and that predicted uncertainties can be related to actual part error uncertainties.
Citation
Journal of Manufacturing Science and Engineering-Transactions of the ASME
Report Number
6868

Keywords

coordinate measuring machine, drilling, error uncertainties, laser ball bar, machine tool errors, machine tools, milling, Monte Carlo, propagation of errors

Citation

Gilsinn, D. and Ling, A. (2002), Comparative Statistical Analysis of Test Parts Manufactured in Production Environments, Journal of Manufacturing Science and Engineering-Transactions of the ASME (Accessed March 29, 2024)
Created June 1, 2002, Updated February 19, 2017