• 한국정밀공학회지
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• 제20권12호
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• pp.34-41
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• 2003

This paper suggests a methodology fur improving the machining accuracy by compensating for the machining errors based on on-machine measurement process. Probing errors and machine tool errors included in the measurement data were calibrated or compensated to obtain the actual machining errors. Machine tool errors were modeled in forward and backward directions according to the axis movement direction to consider the effects of backlash errors on the measurement data, and model parameters were determined by measuring a cube array artifact. A rectangular workpiece was machined and then measured with a touch probe as a verification experiment. Machining experiments showed that the machining errors were reduced to within the designated tolerance after compensating for the actual machining errors by modifying the original footpath for the next-step machining.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 춘계학술대회
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• pp.1352-1357
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• 2004

Thermal error compensation has been developed for CNC (Computer Numerical Control) machining center with moving heat sources. The thermal error in CNC machining center has an effect on machining accuracy more than the geometric error does. Thus, temperature distributions of a spindle unit have been analyzed numerically by a Finite Differential Method and experimentally by an infrared (IR) camera in this study. A multiple variable method has been derived to estimate the thermal deformation of the machine origin stably and effectively after measuring deformation and temperature data. The experimental results for a vertical machining center have shown that the thermal errors of the machine origins were reduced more than 30% by the developed method.

• 한국기계가공학회지
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• 제20권7호
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• pp.15-24
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• 2021

In this paper, to analyze the types of surface morphology error according to factors that cause machining error, the experiments were conducted in the ultra-precision diamond machine using a diamond tool. The factors causing machining error were classified into the pressure variation of compressed air, external shock, tool errors, machining conditions (rotational speed and feed rate), tool wear, and vibration. The pressure variation of compressed air causes a form accuracy error with waviness. An external shock causes a ring-shaped surface defect. The installed diamond tool for machining often has height error, feed-direction position error, and radius size error. The types of form accuracy error according to the tool's errors were analyzed by CAD simulation. The surface roughness is dependent on the tool radius, rotational speed, and feed rate. It was confirmed that the surface roughness was significantly affected by tool wear and vibration, and the surface roughness of Rz 0.0105 ㎛ was achieved.

• 한국기계가공학회지
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• 제12권5호
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• pp.36-41
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• 2013

One of the problems in grinding process using a machining center(MC) with a small diametric wheels is machining error due to decrease of the quill diameter. In this study, side-cut grinding is performed with a vitrified bonded CBN wheel on the machining center. Grinding experiments are performed at various grinding conditions including quill length, quill diameter and depth of cut. The effect on the grinding force, machining error and surface roughness due to the change of the quill rigidity are investigated experimentally. The slenderness ratio of the quill is significant factor to analyse the change of the grinding force and machining error.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.376-381
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• 2001

This paper presents a methodology of machining error compensation by using Artificial Neural Network(ANN) model based on the inspection database of On-Machine-Measurement(OMM) system. First, the geometric errors of the machining center and the probing errors are significantly reduced through compensation processes. Then, we acquire machining error distributions from a specimen workpiece. In order to efficiently analyze the machining errors, we define two characteristic machining error parameters. These can be modeled by using an ANN model, which allows us to determine the machining errors in the domain of considered cutting conditions. Based on this ANN model, we try to correct the tool path in order to effectively reduce the errors by using an iterative algorithm. The iterative algorithm allows us to integrate changes of the cutting conditions according to the corrected tool path. Experimentation is carried out in order to validate the approaches proposed in this paper.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.425-428
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• 1997

Effectiveness of corrective machining algorithm is verified experimentally in this paper by performing corrective lapping work to single side and double sides hydrostatic tables. Lapping is applied as machining method. Machining information is calculated from measured motion errors by applying the algorithm, without information on rail profile. It is possible to acquire 0.13pm of linear motion error, 1.40arcsec of angular motion error in the case of single side table, and 0.07pm of linear motion error, 1.42arcsec of angular motion error in the case of double sides table. The experiment is performed by the unskilled person after he experienced a little of preliminary machining. Experimental results show that corrective machining algorithm is very effective, and anyone can improve the accuracy of hydrostatic table by using the algorithm.

• 한국공작기계학회논문집
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• 제15권4호
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• pp.92-97
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• 2006

This paper presents an integrated machining error compensation method based on PNN(Polynomial Neural Network) approach and inspection database of OMM(On-Machine-Measurement) system. To efficiently analyze the machining errors, two machining error parameters are defined and modeled using the PNN approach, which is used to determine machining errors for the considered cutting conditions. Experiments are carried out to validate the approaches proposed in this paper. In result, the proposed methods can be effectively implemented in a real machining situation, producing much fewer errors.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.581-582
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• 2006

This paper presents an integrated machining error compensation method based on PNN(Polynomial Neural Network) approach and inspection database of OMM(On-Machine-Measurement) system. To efficiently analyze the machining errors, two machining error parameters are defined and modeled using the PNN approach, which is used to determine machining errors for the considered cutting conditions. Experiments are carried out to validate the approaches proposed in this paper. In result, the proposed methods can be effectively implemented in a real machining situation, producing much fewer errors.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.748-754
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• 1994

This paper deals with a geometric error simulator, measurement and inspection of workpiece errors on the machine tools, and identification and compensation methodology of thermal errors in machining centers. In order to raise the machining accuracy of workpieces a measurement and inspection system on the machine tool is developed. By using MPPGT module Manual and CNC type CMMs are realized on the machining centers. To compensate for geometric and thermal deformation errors of machining centers, a real time and an off line geometric adaptive control system were developed on the machining centers. A vertical and a horizontal machining center equipped with FANUC 0MC were used for experiments. Performance of the systems were confirmed with a large amount of experiment.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.721-724
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• 2000

This paper presents a prediction of tool deflection and resulting machining error fur sculptured surface productions in the ball-end milling process. Due to the different materials and the dimensions of the tool holder and cutter, a cantilever hem model with three uniform sections is proposed fur the tool deflection model. The ability of this model has been verified by a machining experiment. In this study, cutting force and machining error are investigated. This paper provides the prediction of machining error for sculptured surface to improve machining quality for industrial application.