Abstract
Cutting force prediction is very important because phenomena occurring during cutting and their resulting outcomes can be predicted and controlled by knowing the cutting forces. The accuracy of predicted cutting forces depends on that of calibration data. Therefore, the accuracy of calibration data needs to be known to estimate the prediction accuracy for cutting forces. In the present study, it is experimentally shown that calibration data used for mechanistic models have a specific probability distribution. A number of calibration data are generated through Monte-Carlo simulation using this probability distribution, resulting in an error index ofcalibration data (MPE) and the relationship between error of the predicted cutting forces and the error index. The results from this error analysis are utilized to estimate the prediction accuracy of the cutting forces and to optimize the calibration procedure that ensures the error in the cutting forces is within a given tolerance. The error analysis made in the present study is very practical because the calibration data accumulated in industry for various cutting processes can be directly utilized for the analysis without any additional experiments.
| Original language | English |
|---|---|
| Pages (from-to) | 149-162 |
| Number of pages | 14 |
| Journal | Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture |
| Volume | 225 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2011 Feb 1 |
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Keywords
- Cutting coefficient
- Cutting force prediction
- Error analysis
- Mechanistic model
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Mechanical Engineering
Cite this
Error analysis of the cutting coefficients and optimization of calibration procedure for cutting force predictiong. / Ahn, I. H.; Hwang, J. H.; Choi, Woo Chun.
In: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 225, No. 2, 01.02.2011, p. 149-162.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Error analysis of the cutting coefficients and optimization of calibration procedure for cutting force predictiong
AU - Ahn, I. H.
AU - Hwang, J. H.
AU - Choi, Woo Chun
PY - 2011/2/1
Y1 - 2011/2/1
N2 - Cutting force prediction is very important because phenomena occurring during cutting and their resulting outcomes can be predicted and controlled by knowing the cutting forces. The accuracy of predicted cutting forces depends on that of calibration data. Therefore, the accuracy of calibration data needs to be known to estimate the prediction accuracy for cutting forces. In the present study, it is experimentally shown that calibration data used for mechanistic models have a specific probability distribution. A number of calibration data are generated through Monte-Carlo simulation using this probability distribution, resulting in an error index ofcalibration data (MPE) and the relationship between error of the predicted cutting forces and the error index. The results from this error analysis are utilized to estimate the prediction accuracy of the cutting forces and to optimize the calibration procedure that ensures the error in the cutting forces is within a given tolerance. The error analysis made in the present study is very practical because the calibration data accumulated in industry for various cutting processes can be directly utilized for the analysis without any additional experiments.
AB - Cutting force prediction is very important because phenomena occurring during cutting and their resulting outcomes can be predicted and controlled by knowing the cutting forces. The accuracy of predicted cutting forces depends on that of calibration data. Therefore, the accuracy of calibration data needs to be known to estimate the prediction accuracy for cutting forces. In the present study, it is experimentally shown that calibration data used for mechanistic models have a specific probability distribution. A number of calibration data are generated through Monte-Carlo simulation using this probability distribution, resulting in an error index ofcalibration data (MPE) and the relationship between error of the predicted cutting forces and the error index. The results from this error analysis are utilized to estimate the prediction accuracy of the cutting forces and to optimize the calibration procedure that ensures the error in the cutting forces is within a given tolerance. The error analysis made in the present study is very practical because the calibration data accumulated in industry for various cutting processes can be directly utilized for the analysis without any additional experiments.
KW - Cutting coefficient
KW - Cutting force prediction
KW - Error analysis
KW - Mechanistic model
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U2 - 10.1243/09544054JEM2006
DO - 10.1243/09544054JEM2006
M3 - Article
VL - 225
SP - 149
EP - 162
JO - Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
JF - Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
SN - 0954-4054
IS - 2
ER -