• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.406-411
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• 1993

A variable structure control scheme that can be applied to the process with input/output delays are proposed and its control performances are evaluated. The proposed VSCS, which is an output fedback scheme, comprises an integrator for tracking the setpoint and the Smith predictor for compensating the effects of time delay. With The VSCS, the robustness against the parameter variations and external disturbances can be achieved even when the controlled process includes I/O delays. And the desired transient response is obtained by simple adjustment of the coefficients of the switching surface equation.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.2
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• pp.125-137
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• 1997

We are concerned with the packing policy determines the optimal packing of products with variable sizes to minimize the penalty costs for idle space and product spliting. Optimal packing problem is closely related to the optimal packet/record sizing problem in that randomly generated data stream with variable bytes are divided into a unit of packet/record for transmitting or storing. Assuming the product size and the production period are independently determined by renewal process, we can approximate the renewal process and formulate the optimization problem that minimize the expected packing cost for a production period. The problem is divided into two cases according to whether a product is allowed to split or not. Computational results for various distributions will be given to verify the approximation procedure and the resulting optimization problem.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.1
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• pp.109-116
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• 2001

The detection of corporate failures is a subject that has been particularly amenable to cross-sectional financial ratio analysis. In most of firms, however, the financial data are available over past years. Because of this, a model utilizing these longitudinal data could provide useful information on the prediction of bankruptcy. To correctly reflect the longitudinal and firm-specific data, the generalized linear model with assuming the first order AR(autoregressive) process is proposed. The method is motivated by the clinical research that several characteristics are measured repeatedly from individual over the time. The model is compared with several other predictive models to evaluate the performance. By using the financial data from manufacturing corporations in the Korea Stock Exchange (KSE) list, we will discuss some experiences learned from the procedure of sampling scheme, variable transformation, imputation, variable selection, and model evaluation. Finally, implications of the model with repeated measurement and future direction of research will be discussed.

• Proceedings of the KWS Conference
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• 2000.04a
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• pp.303-306
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• 2000

Quality estimation of the weld has been one of the important issues in RSW which is a main process of the sheep metal fabrication in auto-body industry, It was well known that among the various welding process variables, dynamic resistance has a close relation with nugget formation. With this variable, it is possible to estimate the weld quality in real time. In this study, a new quality estimation algorithm is developed with the primary dynamic resistance measured at welding machine timer. For this, feature recognition method of Hopfield neural network is used. Primary resistance patterns are vectorized and classified with five patterns. The network trained by these patterns recognizes the dynamic resistance pattern and estimates the weld quality Because the process variable monitored at the primary circuit is used, it is possible to apply this system to real time application without any consideration of electrode wear or shunt effect.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.2
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• pp.114-122
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• 2004

In statistical process control applications, variable sample size (VSS) $\bar{X}$ chart is often used to detect the assignable cause quickly. However, it is usually assumed that only one assignable cause results in the out-of-control in the process. In this paper, we propose the algorithm to minimize the function of cost per unit time and compare the economic design and the statistical design by use of the value of cost per unit time. We consider double assignable causes to occur with compound in the process and adopt the Markov chain approach to investigate the statistical properties of VSS $\bar{X}$ chart. A procedure that can calculate the control chart's parameters is proposed by the economic design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.309-330
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• 2009

In this paper, we introduce the architecture of Genetic Algorithm(GA) based Feed-forward Polynomial Neural Networks(PNNs) and discuss a comprehensive design methodology. A conventional PNN consists of Polynomial Neurons, or nodes, located in several layers through a network growth process. In order to generate structurally optimized PNNs, a GA-based design procedure for each layer of the PNN leads to the selection of preferred nodes(PNs) with optimal parameters available within the PNN. To evaluate the performance of the GA-based PNN, experiments are done on a model by applying Medical Imaging System(MIS) data to a multi-variable software process. A comparative analysis shows that the proposed GA-based PNN is modeled with higher accuracy and more superb predictive capability than previously presented intelligent models.

• Journal of Welding and Joining
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• v.10 no.2
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• pp.32-42
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• 1992

A method of optimization of process parameters in Arc Welding has been discussed in this paper. The method of investigation is based on the numerical calculation of weld bead by a finite element method and non-linear optimization technique is applied to estimated the optimization process parameters from the numerical calculation. The common package program(ANSYS 4.4A) was used to obtain the process parameters for a thin plate arc welding (TIG, CO$_{2}$). The results on some test are satisfactory and the used method of this paper is a useful guide to the optimum welding condition.

• Journal of Welding and Joining
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• v.32 no.2
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• pp.43-47
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• 2014

Famous artificial neural network (ANN) is applied to predict proper process window of arc welding. Target weldment is variously combined lap joint fillet welding of automotive steel plates. ANN's system variable such as number of hidden layers, perceptrons and transfer function are carefully selected through case by case test. Input variables are welding condition and steel plate combination, for example, welding machine type, shield gas composition, current, speed and strength, thickness of base material. The number of each input variable referred in welding experiment is counted and provided to make it possible to presume the qualitative precision and limit of prediction. One of experimental process windows is excluded for predictability estimation and the rest are applied for neural network training. As expected from basic ANN theory, experimental condition composed of frequently referred input variables showed relatively more precise prediction while rarely referred set showed poorer result. As conclusion, application of ANN to arc welding process window derivation showed comparatively practical feasibility while it still needs more training for higher precision.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.481-483
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• 1998

In general, spatial filtering method was proposed to simplify measurement system through parallel Processing hardware. Spatial filtering is a method of detection that we can get a spatial pattern information, as we process a special space pattern, to say, as we process spatial parallel process by using the spatial weighting function. The important processing characteristics will be depended in according to how ire design a spatial weighting function, a spatial sensitive distribution. The form of the weighting function which is realized from the generally used spatial filtering is fixed and the weighting value was already became a binary-value. In this paper, we propose a new method in order to construct adaptive measurement systems. This method is a weighting function design to make multi-valued and variable.

• Journal of Families and Better Life
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• v.20 no.1
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• pp.115-124
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• 2002

The purpose of this study is to examine the social competence of children with reference to day care center's structural, process variables and demographic variables. The subjects were 156 children who attend day care center, aged from 3 to 5 years and 9 teachers in Seoul or the province of KyungkiDo. Data were gathered via the structured Questionnaires distributed to the teachers to rate children's social competence and their own job satisfaction. And two observers rated teacher-child interaction in day care center The major findings are as follows The variables predicting children's social competence were child's sex, age, period of attendance in day care center, teacher's job satisfaction, and group size. Especially this study suggests that teachers who are highly satisfied with their job and small group size influence children's social competence positively.