• Journal of the Korean Society for Precision Engineering
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• v.28 no.8
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• pp.904-914
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• 2011

The volumetric errors of CNC machining centers are determined by 21 errors, including 3 linear errors, 6 straightness errors, 3 perpendicular errors, 9 angular errors and non-rigid body errors of the machine tool. It is very time consuming and hard to measure all of these errors in which laser interferometer and other parts are used directly. Hence, as many as 21 separate setups and measurements are needed for the linear, straightness, angular and perpendicular errors. In case of the 5-axis machining centers, two more rotary tables are used. It can make 35 error sources of the movement. Therefore, the measured errors of multi movements of the 5-axis tables are very complicated, even if the relative measured errors are measured. This paper describes the methods, those analyze the error sources of the machining centers. Those are based on shifted diagonal measurements method (SDM), R-test and Double ball bar. In case, the angular errors of machine are small enough comparing with others, twelve errors including three linear position errors, six straightness errors and three perpendicular errors can be calculated by using SDM. To confirm the proposed method, SDM was applied to measuring 3 axes of machine tools and compared with directly measurement of each errors. In addition, the methods for measuring relative errors of multi-axis analysis methods using R-test and Double Ball Bar are introduced in this paper.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.227-234
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• 2002

This study was conducted to nondestructively estimate the volumetric information of peach and pit and to visualize the 3D information of internal structure from magnetic resonance imaging(MRI) data. Bruker Biospec 7T spectrometer operating at a proton reosonant frequency of 300 MHz was used for acquisition of MRI data of peach. Image processing algorithms and visualization techniques were implemented by using MATLAB (Mathworks) and Visualization Toolkit(Kitware), respectively. Thresholding algorithm and Kohonen's self organizing map(SOM) were applied to MRI data fur region segmentation. Volumetric information were estimated from segemented images and compared to the actual measurements. The average prediction errors of peach and pit volumes were 4.5%, 26.1%, respectively for the thresholding algorithm. and were 2.1%, 19.9%. respectively for the SOM. Although we couldn't get the statistically meaningful results with the limited number of samples, the average prediction errors were lower when the region segmentation was done by SOM rather than thresholding. The 3D visualization techniques such as isosurface construction and volume rendering were successfully implemented, by which we could nondestructively obtain the useful information of internal structures of peach.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.7
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• pp.98-105
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• 2001

The machining accuracy is affected by geometric, volumetric errors of the machine tools. To improve the product quality, we need to enhance the machining accuracy of the machine tools. To this point of view, measurement and inspection of finished part as error analysis of machine tools ahas been studied for last several decades. This paper suggests the enhancement method of machining accuracy for precision machining of high quality metal reflection mirror or optics lens, etc. In this paper, we study 1) the compensation of linear pitch error with NC controller compensation function using laser interferometer measurement, 2) the method for enhancing the accuracy of NC milling machining by modeling and compensation of volumetric error, 3) the spherical surface manufacturing by modeling and compensation of volumetric error of the machine tool, 4) the system development of OMM without detaching work piece from a bed of machine tool after working, 5) the generation of the finished part profile by OMM. Furthermore, the output of OMM is compared with that of CMM, and verified the feasibility of the measurement system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.632-635
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• 2002

In this paper, a general procedure to determine machine tool errors from the on-machine measurement (OMM) data is described. First, a parameterized error model of a machine tool is illustrated by approximating error components as linear function of axis positions, and a modified error model is proposed which includes backlash effects. To determine the unknown model coefficient vectors of the forward and backward error model, an artifact with 8 cutes is made and calibrated on CMM. Then, lower-left and upper-right cube corners are measured with a touch-trigger probe mounted on the machine tool spindle. Measured error data are used to determine the coefficient vectors. The positioning errors in the XY plane at the fixed z position are simulated for the forward and backward error model.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.453-457
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• 2001

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric and thermal errors of the machine tools. In this study, the compensation device is manufactured in order to compensate thermal error of machine tools under the real-time. This paper models of the thermal errors for error analysis and develops on-the-machine measurement system by which the volumetric error are measured and compensated. The thermal error is modeled by means of angularity errors of a column and thermal drift error of the spindle unit which are measured by the touch probe unit with a star type styluses, a designed spherical ball artifact, and five gap sensors. In order to compensate thermal characteristics under several operating conditions, experiments performed with five gap sensors and manufactured compensation device on the horizontal machining center.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.439-442
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• 2001

The Accuracy of a free-form artifact is affected by machine tool errors, machining process errors, environmental causes and other uncertainty. This paper deals with methodological approach about machine tool errors that are defined the relationship between CMM and OMM inspections of the free-form artifact. In order to analyze the measurement data, Reverse engineering was used. In other words, Surface of Free-Form Artifact is generated by NURBS surface approximation method. Finally, Volumetric error map is made to compare surface of CMM data with that of OMM data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.621-628
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• 2000

A kinematic ball bar measuring system can analyze the various errors of a machine tool easil rapidly with only one measurement, But it cannot be used to measure the errors of the equipment the semiconductor manufacturing (e.g. chip mounter, PCB router etc.) not to use a cir interpolation. This paper presents the method to apply a kinematic ball bar measuring system tc machines which use merely a linear interpolation Also, the work of measuring and calibratir various errors of a chip mounter with a kinematic bal1 bar measurement system is accomplished

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2589-2596
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• 2000

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model, etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcomes limitation of accuracy in the linear regression model or the engineering judgment model. It shows that the fuzzy model has more better performance than linear regression model, though it has less number of thermal variables than the other. The fuzzy model does not need to have complex procedure such like multi-regression and to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Also, the fuzzy model can be applied to any machine, but it delivers greater accuracy and robustness.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.75-80
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• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.839-840
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• 2012

본 논문에서는 3 축 기계장비의 공간오차를 예측하기 위한 사전 단계로 각 축에 대하여 레일형상오차를 측정하였다. 전용 측정지그를 설계/제작하여 이 지그가 이동함에 따라 혼합축차이점법을 이용하여 레일형상오차를 측정하였다. 레일형상오차로부터 테이블 운동오차를 예측하고, 이와 더불어 각 축 사이의 직각도 오차를 측정한 후 이로부터 최종적으로 3 축 장비에 대한 공간오차를 평가할 예정이다. 예측된 공간오차는 실제 레이저를 이용한 공간오차 측정방법을 이용하여 검증할 예정이다.