• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.159-166
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• 2005

This study deals with the correction of gear tooth profile error by finish roll forming. First, we experimentally confirmed that the tooth profile error is a synthesis of the concave error and the pressure angle error. Since various types of tooth profile errors appear in the experiments, we introduced evaluation parameters for rolling gears to objectively evaluate profile quality. Using these evaluation parameters, we clarified the relationship among the tooth profile error, the addendum modification factor (A. M. factor), and the tool loading force. We verified the character of concave error, pressure angle error, tool loading force and number of cycles of finish roll forming by using a forced displacement method. This study makes clear that tool loading force and number of cycles of finish roll forming are very important factors that affect involute tooth profile error. The results of the experiment and analysis show that the proposed method reduces concave and pressure angle errors.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.633-645
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• 2018

Gaussian error distributions are a common choice in traditional regression models for the maximum likelihood (ML) method. However, this distributional assumption is often suspicious especially when the error distribution is skewed or has heavy tails. In both cases, the ML method under normality could break down or lose efficiency. In this paper, we consider the log-concave and Gaussian scale mixture distributions for error distributions. For the log-concave errors, we propose to use a smoothed maximum likelihood estimator for stable and faster computation. Based on this, we perform comparative simulation studies to see the performance of coefficient estimates under normal, Gaussian scale mixture, and log-concave errors. In addition, we also consider real data analysis using Stack loss plant data and Korean labor and income panel data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.417-418
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• 2007

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.641-653
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• 2022

Penalized least squares methods are important tools to simultaneously select variables and estimate parameters in linear regression. The penalized maximum likelihood can also be used for the same purpose assuming that the error distribution falls in a certain parametric family of distributions. However, the use of a certain parametric family can suffer a misspecification problem which undermines the estimation accuracy. To give sufficient flexibility to the error distribution, we propose to use the symmetric log-concave error distribution with LASSO penalty. A feasible algorithm to estimate both nonparametric and parametric components in the proposed model is provided. Some numerical studies are also presented showing that the proposed method produces more efficient estimators than some existing methods with similar variable selection performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.803-806
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• 1995

The vibration and nosic of gears is causeed by manufacting error,alignment error in assembly, and thr meshing stiffness of gears which changes periodically as the meshing of teeth process. On a pair of power transmission helical gears with profile error, the relation between the characteristics of gear vibration and the profile error type have been investigated by simulating the vibrational acceleration level and calculating the natural frequency. The results show that the profile error decrease the natural frequency by reducing the tool stiffness and that the concave error type increase the vibrationsl level. And this paper describes the effect of the tip relief on the vibrational acceleration level which a pair of helical gears with concave error generates.

• Journal of the Korean Society of Safety
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• v.23 no.4
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• pp.13-18
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• 2008

This study deals with finish roll forming by forced displacement can be conceived as a method of eliminating errors in conventional form rolling under constant loads. This method produces a high-precision tooth profile by low-speed form rolling when a high rigid screw or cam is used at the pressurized section. Tooth profile is decided in the beginning of roll forming and ${\delta}_{max}$ mainly increases if the number of roll forming process is increased. Gear class is improved by one or two class after roll forming if the gear has convex type error and pressure angle error in KS 4 class. If the gear have concave type error and pressure angle error and pressure angle error, gear class is not improved in theory, but improved a little in practice. In the finishing roll forming, it inevitably yields both the concaving of tooth profile and plastic deflection of addendum of teeth. Experiments show that the concaving and the plastic deflection are successfully reduced, the accuracy of tooth profile reaches to KS 0 class.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.2
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• pp.10-17
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• 2004

A real depth of cut in deformed zone has larger than an ideal depth of cut. So the heat generated during grinding operation makes the deformation of a workpiece surface as convex farm. Consequently the workpiece surface remains a geometric error as concave form after cooling In this study, the grinding force and the geometric error were examined in surface grinding. Through magnitude and mode of geometric error were evaluated according to grinding conditions, an optimal grinding condition was proposed to minimize the geometric error In addition, the relationship between the geometric error and the grinding force was examined. Due to least square regression, It was possible to predict the geometric error by using the grinding force.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.2
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• pp.9-16
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• 2004

Because a generated heat during grinding operation makes a serious deformation on a ground surface as a convex form, a real depth of cut in deformed zone has larger than an ideal depth of cut. Consequently, the ground surface has a geometric error as a concave form after cooling the workpiece. In this study, the force and the geometric error of surface grinding were examined. From evaluating magnitude and mode of the geometric error according to grinding conditions, an optimal grinding condition was proposed to minimize the geometric error. In addiction the relationship between the geometric error and the grinding force was found out. Due to least square regression it was able to predict the geometric error by using the grinding force.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.5
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• pp.34-42
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.895-898
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• 2003

The higher precision is demanded in modem manufacturing and it requires the more accurate servo controller. Cross-coupling control (CCC) has been developed to improve contouring motion. In this paper we introduce a new nonlinear CCC that is based on contour-error-vector using a parametric curve interpolator. A vector from the actual tool position to the nearest point on the desire path is directly adopted. The contour-error-vector is determined by constructing a tangential vector of nearest point on desired curve and determining the vector perpendicular to this tangential vector from the actual tool position. Moreover, the vector CCC can apply directly and easily to free-form curves include convex and concave form. The experimental results on a three-axis CNC machine center show that the present approach significantly improves motion accuracy in multi-axis motion