• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.267-267
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• 1998

• Proceedings of the Korean Society for Information Management Conference
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• 1994.12a
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• pp.19-22
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• 1994

the Term Dependence Models has been examined in vew of the theoretical aspects. For the feasibility of these models in an operational system, the parameter estimation problem and other alternative solution has been included.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.263-271
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• 1990

In this paper, we shall construct a ridge estimator in a multiple linear model with the correlated error structure. The existence of the biasing parameter satisfying the Mean Squared Error Criterion is also proved. Furthermore, we shall determine the value of shrinkage factors by the iteration method.

• Journal of Korean Society for Quality Management
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• v.15 no.2
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• pp.61-68
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• 1987

This paper considers the estimation of the parameters of a normal population from which a sample which has been censored at a known point is obtained. Simple estimators are presented which are given in closed forms. It is shown that maximum likelihood estimators are obtained by using the estimation procedure iteratively. Some computer simulation results are given.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.555-558
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• 2002

Sales Rate is a key parameter whose indications on real estate market plays a key role in prospecting and establishing governmental policies and strategies for Condominiums. However, it's not easy to present systematic model for tracing the effects of this parameter on sales rate without definite concept and relations with sales rate. Therefore, this study (1) derives factors affecting Sales Rate of Condominiums, (2) specially, gives an analysis of correlation with variable for the rest of factors based on economic factors, and then finds out its influential relation, (3) presents diagrammatic analysis model of all impact variables by factor to grasp on the whole for Sales Rate of Condominiums.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

• Journal of Korean Society for Quality Management
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• v.24 no.3
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• pp.111-132
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• 1996

Taguchi's parameter design is to determine optimal settings of design parameters of a product or a process such that the characteristics of a product exhibit small variabilities around their target values. His analysis of the problem has focused only on a single characteristic or response, but the quality of most products is seldom defined by a characteristic, and is rather the composite of a great number of characteristics which are often interrelated and nearly always measured in a variety of units. The critical problem in dealing with multiple characteristics is how to compromise the conflicts among the selected levels of the design parameters for each individual characteristic. In this paper, the EXTOPSIS Model using SN ratio which can be optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Two existing case studies are solved by the proposed method and the results are compared with ones by the sum of SN ratios, the expected weighted loss, and the desirability function.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.25-32
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• 2017

For repairable software systems, the Mean Time Between Failure (MTBF) is used as a measure of software system stability. Therefore, the evaluation of software reliability requirements or reliability characteristics can be applied MTBF. In this paper, we want to compare MTBF in terms of parameter estimation using Makeham life distribution. The parameter estimates used the least square method which is regression analyzer method and the maximum likelihood method. As a result, the MTBF using the least square method shows a non-decreased pattern and case of the maximum likelihood method shows a non-increased form as the failure time increases. In comparison with the observed MTBF, MTBF using the maximum likelihood estimation is smallerd about difference of interval than the least square estimation which is regression analyzer method. Thus, In terms of MTBF, the maximum likelihood estimation has efficient than the regression analyzer method. In terms of coefficient of determination, the mean square error and mean error of prediction, the maximum likelihood method can be judged as an efficient method.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.58-67
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• 2002

Since the inception of off-line quality control, it has drawn a particular attention from research community and it has been implemented in a wide variety of industries mainly due to its extensive applicability to numerous real situations. Emphasizing design issues rather than control issues related to manufacturing processes, off-line quality control has been recognized as a cost-effective approach to quality improvement. It mainly consists of three design stages: system design, parameter design, and tolerance design which are implemented in a sequential manner. Utilizing experimental designs and optimization techniques, off-line quality control is aimed at achieving product performance insensitive to external noises by reducing process variability. In spite of its conceptual soundness and practical significance, however, off-line quality control has also been criticized to a great extent due to its heuristic nature of investigation. In addition, it has also been pointed out that the process optimization procedures are inefficient. To enhance the current practice of off-line quality control, this study proposes an integrated optimization model by utilizing a well-established statistical tool, so called response surface methodology (RSM), and a tolerance - cost relationship.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.135-148
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• 2024

Purpose: This study is to investigate the literature on accelerated tests based on the acceleration model and to provide a compilation of results on the parameters applied in the acceleration model and the test conditions. Methods: This research is conducts a literature review on accelerated tests using the acceleration model, with a focus on test targets, test conditions, and parameter values. The study is organizing the results of this literature review to facilitate their application in the design of reliability tests. Results: A literature review investigated a variety of test targets, test conditions, and parameter values. Conclusion: The results of the literature research conducted revealed various acceleration model parameter. Such literature research on accelerated tests can establish the foundation for reliability test design and contribute to future product development and quality improvement