• Transactions of Materials Processing
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• v.27 no.1
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• pp.28-36
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• 2018

Electromagnetic forming is a type of high-speed forming process to deform a workpiece through a Lorentz force. As the high strain rate in an electromagnetic-forming simulation causes infeasibility in determining constitutive parameters, we employed inverse parameter estimation in the previous study. However, the inverse parameter estimation process required us to spend considerable time, which leads to an increase in computational cost. To overcome the computational obstacle, in this research, we applied two types of surrogate modeling methods and compared them to each other to evaluate which model is best for the electromagnetic-forming simulation. We exploited an artificial neural network and we reduced-order modeling methods. During the construction of a reduced-order model, we extracted orthogonal bases with proper orthogonal decomposition and predicted basis coefficients by utilizing an artificial neural network. After the construction of the surrogate models, we verified the artificial neural network and reduced-order models through training and testing samples. As a result, we determined the artificial neural network model is slightly more accurate than the reduced-order model. However, the construction of the artificial neural network model requires a considerably larger amount of time than that of the reduced-order model. Thus, a reduced order modeling method is more efficient than an artificial neural network for estimating the electromagnetic forming and for the rapid approximation of structural simulations which needs repetitive runs.

• Journal of Korean Society for Quality Management
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• v.41 no.1
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• pp.109-118
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• 2013

Purpose: Given the several proper models for given mixture components-process variables experimental data, we propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those models. Methods: Given the mixture experimental data with process variables, first we choose the reasonable starting models among the class of admissible product models based on the model selection criteria and then, search for the candidate models that are the subset models of the starting model by the sequential variable selection method or all possible regressions procedure. Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. Results: We propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those good candidate models by adopting the optimization methods developed in multiple responses surface methodology. Conclusion: A strategy is proposed to find the optimal condition in which the performance of the responses is well-behaved under those proper combined models. This strategy to find the optimal condition is illustrated with the example in this paper.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.223-228
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• 2022

In chemical processes, unintended faults can make serious accidents. To tackle them, proper fault diagnosis models should be designed to identify the root cause of faults. To design a fault diagnosis model, a process and its data should be analyzed. However, most previous researches in the field of fault diagnosis just handle the data set of benchmark processes simulated on commercial programs. It indicates that it is really hard to get fresh data sets on real processes. In this study, real faulty conditions of an industrial polystyrene process are tested. In this process, a runaway reaction occurred and this caused a large loss since operators were late aware of the occurrence of this accident. To design a proper fault diagnosis model, we analyzed this process and a real accident data set. At first, a mode classification model based on support vector machine (SVM) was trained and principal component analysis (PCA) model for each mode was constructed under normal operation conditions. The results show that a proposed model can quickly diagnose the occurrence of a fault and they indicate that this model is able to reduce the potential loss.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.697-707
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• 2017

In this paper, we propose a modified GARCH(p, q)-X model which is obtained by adding the exogenous variables to the modified GARCH(p, q) process. Some limiting properties are shown under various stationary and nonstationary exogenous processes which are generated by another process independent of the noise process. The proposed model extends the GARCH(1, 1)-X model studied by Han (2015) to various GARCH(p, q)-type models such as GJR GARCH, asymptotic power GARCH and VGARCH combined with exogenous process. In comparison with GARCH(1, 1)-X, we expect that many stylized facts including long memory property of the financial time series can be explained effectively by modified GARCH(p, q) model combined with proper additional covariate.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.8 no.1
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• pp.1-7
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• 2012

A PHE (Process Heat Exchanger) is a key component required to transfer heat energy of $950^{\circ}C$ generated in a VHTR (Very High Temperature Reactor) to the chemical reaction that yields a large quantity of hydrogen. A small-scale PHE prototype made of Hastelloy-X is being tested in a small-scale gas loop at Korea Atomic Energy Research Institute. In order to properly evaluate the high-temperature structural integrity of the small-scale PHE prototype, it is very important to impose a proper constraint condition on its structural analysis model. For this effort, we tried to impose several constraint conditions on the structural analysis model and consequently fixed a proper and effective displacement constraints.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.3
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• pp.83-91
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• 1999

In order to build and manage an ATM network effectively under several types of control methods, it is necessary to estimate the performance of the equipments in various viewpoints, especially of ATM multiplexer. As for the method to model the input stream into the ATM multiplexer, many researches have been done to characterize it by, such as, fluid flow, MMPP(Markov Modulated Poisson Process), or MMDP (Markov Modulated Deterministic Process). We introduce an MRP(Markov Renewal Process) to model the input stream which has proper structure to represent the burst traffic with high correlation. In this paper, we build a model for aggregated heterogeneous ON-OFF sources of ATM traffic by MRP. We make discrete time MR/D/1/B queueing system, whose input process is the superposed MRP and present a performance analysis by finding CLP(Cell Loss Probability). A simulation is done to validate our algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.1
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• pp.111-111
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• 1987

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

• Korean Management Science Review
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• v.12 no.1
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• pp.111-124
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• 1995

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

• Proceedings of the Korea Association of Crystal Growth Conference
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• 1997.10a
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• pp.117-121
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• 1997

It is shown theoretically that uniform axial dopant concentration distribution can be made throughout the crystal by continuous Czochralski process. Numerical simulation are performed for the transient two-dimensional convection-diffusion model. A typical value of the growth and system parameters for Czochralski growth of p-type, 4 inches silicon crystal was used in the numerical calculations. Using this model with proper model parameter, the axial segregation in batchwise Czochralski growth can be described. It is studied by comparing with the experimental data. With this model parameter, the uniform axial concentration distribution of dopant is predicted in continuous Czochralski process.

• Journal of Information Technology Services
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• v.6 no.3
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• pp.87-110
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• 2007

Recently, researches on IT Service Management (ITSM) for improving information system operation service and information system outsourcing cost estimation model are proliferating. This study suggests a new cost model of IT operation service and optimizing method based upon the characteristics of operation service as a long-term and continuous business service for both user's and service provider's point of view. This study explains the cost optimization model of IT operation service by improving service request management process, such as adequate reception and control, proper valuation, process management using project management methodology, effective organization and time management of service personnel. Especially in this study, service ability improvement effect and fixed operation cost reduction effect are defined to prove the proposed new cost model.