• Journal of Korean Society for Quality Management
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• v.37 no.2
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• pp.46-57
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• 2009

The traditional approach to economic design of control charts is based on the assumption that a process is monitored using a performance variable. However, various types of automatic test equipments recently introduced as a part of factory automation usually measure surrogate variables instead of performance variables that are costly to measure. In this article we propose a model for economic design of a control chart which uses a surrogate variable that is highly correlated with the performance variable. The optimum values of the design parameters are determined by maximizing the total average income per cycle time. Numerical studies are performed to compare the proposed $\bar{X}$ control charts with the traditional model using the examples in Panagos et al. (1985).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1141-1145
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• 2016

In general, a variable forgetting factor is applied to the RLS algorithm for the time-varying parameter estimation in the non-stationary environments. The introduction of a variable forgetting factor to RLS needs heavy additional calculation complexity. We propose a new Gauss Newton variable forgetting factor RLS algorithm which needs small amount of calculation as well as estimates the better parameters in time-varying nonstationary environment. The algorithm performs as good as the conventional Gauss Newton variable forgetting factor RLS and the required additional calculation complexity reduces from $O(N^2)$ to O(N).

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.360-364
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• 2001

In this paper, a novel method of reaching law variable structure control based on fuzzy rules is present, which is that the reaching law parameters is on-line adjusted by fuzzy rules. This method is used in a digital ac position servo system, the experiment results show that the system designed by this method has both satisfactory quality and very smaller chattering.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.907-914
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• 1999

This paper studies on the model identification of electro-hydraulic servo systems, which are composed of servo valves, double-rod cylinder and load mass. The identified plant is described as a discrete-time ARX or ARMAX model which is respectively obtained from the identification algorithms of least square error method, instrumental variable method and prediction error method. where a nominal model and the variation of model parameters are quantitatively evaluated.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.31-39
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• 2001

For estimating parameters of possibly nonlinear and/or non-stationary seasonal autoregressive(AR) processes, we introduce a new instrumental variable method which use the direction vector of the regressors in the same period as an instrument. On the basis of the new estimator, we propose new seasonal random walk tests whose limiting null distributions are standard normal regardless of the period of seasonality and types of mean adjustments. Monte-Carlo simulation shows that he powers of he proposed tests are better than those of the tests based on ordinary least squares estimator(OLSE).

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.3
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• pp.116-122
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• 2003

This paper proposes an efficient method for computing the 3-dimensional capacitance of complex structures. The proposed method Is based on Finite Element Method(FEM) and expands the conventional FEM by adopting variable division. This method improves the extraction efficiency 50 times when compared to the conventional FEM with equal division. The proposed method can be used efficiently to extract electrical parameters of on/off-chip interconnects in VLSI systems.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1133-1138
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• 1991

A control of nonlinear system is motivated by the fact that all real plants are nonlinear systems and model identification introduces parameter errors. The purpose of this study is to design a Discrete Variable Structure Controller(DVSC) for single-rod hydraulic cylinder system. The model contains uncertain parameters which we known to lie upper and lower bounds. In the design of DVSC, the boundary layer concept was adopted to reduce cattering. The DVSC was evaluated through digital computer simulation and compared with a VSC (analog controller).

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.353-356
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• 2001

This paper proposes an efficient method for 3-dimensional capacitance extraction based on Finite Element Method(FEM). This method expands the conventional FEM by adopting variable division. This method improves the extraction efficiency 2 to 100 times and even the accuracy 1% to 3% when compared to the conventional FEM with equal division. The Proposed method can be used efficiency to extract electrical parameters of on/off-chip interconnects in VLSI systems.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.145-152
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• 1994

This paper deals with an economic design of acelerated life test under constant stresses where failure times are exponentially distributed. In this case the optimization criterion is the information amount per unit cost. Fisher's information matrix of exponential distribution's parameters and expected cost considering fixed and variable costs are obtained. The decision variable is the censoring time in the model. In the 2-level constant stress case, it is proved that the optimal solution exists and is unique under some condition. Numerical examples are also included.

• Journal of the military operations research society of Korea
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• v.25 no.2
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• pp.158-169
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• 1999

This paper is concerned with the application of generalized linear interactive modelling(GLIM) to the binary categorical data. To analyze the categorical data given by a contingency table, finding a good-fitting loglinear model is commonly adopted. In the case of a contingency table with a response variable, we can fit a logit model to find a good-fitting loglinear model. For a given $2^4$ contingency table with a binary response variable, we show the process of fitting a loglinear model by fitting a logit model using GLIM and SAS and then we estimate parameters to interpret the nature of associations implied by the model.