• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.113-125
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• 1995

This paper describes the 2-stage randomized response model in the Bayesian view point. The classical Bayesian analysis needs the complete information for a prior density, but the Bayes linear estimator needs only the first and second moments. Therefore, it is convenient to find the estimator and this estimator robusts to a prior density. We show that MSE's of the Bayes linear estimators for the 2-stage randomized response models are smaller than those of the MLE's for the 2-stage randomized response models.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.384-386
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• 2002

As restructuring in power industry has introduced competitive markets, a new method on demand side management has been developed. Many programs using the method were developed with providing several choices for customer. Nowadays the programs are called demand response as the load management is done by customer's responding to the market price signal. It was proven that the method was effective for demand control with the active consumer's attending for the program. This paper analyses the perspective and the requirement for designing the demand response system.

• Journal of Korean Society for Quality Management
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• v.7 no.2
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• pp.22-28
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• 1979

The problem considered in this paper is to select the vital factor effect to the product quality through the experimental design and analysis of response surface, so as to control the quality improvement of industrial product. In this time, even through the mathematical model is unknown it could be applicable to control the quality of industrial products and to determine optimum operating condition for many technical fields, particulary, for industrial manufacturing process. When a set of data is available from an experimental design, it is often of interest 1:0 fit polynominal repression model in independent variables (eg, time, temperature, pressure, etc) the optimize the response variable (eg. yield, strength etc). This paper proposes a method known to obtain the optimum operating condition, and how to find the condition by using table of orthogonal array experiments, and optimization methodology of statistical model. A criterion can be applied determining to optimum operating conditions in manufacturing industry and improving the fit of response surface which may be used for prediction of responses and quality control of industrial products.

• Proceedings of the Korean Society for Quality Management Conference
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• 2009.10a
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• pp.15-22
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• 2009

Quality variations in mixture products such as medicine, food, engineering chemicals, and alloy materials can be caused by their own sub-components. For instance, discharging characteristics of a lithium-ion rechargeable battery depend upon the mixture ratio of ethylene, dimethyle, and ethyle-methyle, all of which consists an electrolyte solution in the battery. Thus it is important to determine tolerances of mixture components in maintaining the product quality at a desired level. This paper proposes a simple but efficient approach to a mixture tolerancing method with multi-response variables. We use a response surface method for empirical modelling between mixture components. An illustrative example of the proposed method is given.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.413-424
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• 2010

Mixture experiments involve combining ingredients or components of a mixture and the response is a function of the proportions of ingredients which is independent of the total amount of a mixture. The purpose of the mixture experiments is to find the optimum blending at which responses such as the flavor and acceptability are maximized. We assume the quadratic or special cubic canonical polynomial model over the experimental region for a mixture since the current mixture is assumed to be located in the neighborhood of the optimal mixture. The cost of the mixture is proportional to the cost of the ingredients of the mixture and is the linear function of the proportions of the ingredients. In this paper, we propose mixture response surface methods to develop a mixture such that the cost is down more than ten percent as well as mean responses are as good as those from the current mixture. The proposed methods are illustrated with the well known the flare experimental data described by McLean and Anderson(1966).

• Health Policy and Management
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• v.28 no.3
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• pp.308-314
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• 2018

Injury is a serious problem that not only causes death but also significantly degrades the quality of life of the people and causes loss of socioeconomic opportunities and costs. Damage occurs as a result of an accident. Among them, natural disasters and artificial disasters take lives of many people in a short time and threaten their physical and mental health. The United States has responded to the disaster by establishing relevant laws and regulations and a response system with the recognition that health is recognised soon to be as national security in the wake of the 9/11 terrorist attacks and the Katrina disaster. It is necessary to build a knowledge infrastructure to train disaster response experts in public health area and to have health competence to cope with disasters.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.123-126
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• 2008

This research develops a methodology for standard design of spatial Database utilizing the disaster ethnography. Especially, the disaster response operation is sensitive to the size of the disaster, location, damage situation, resource a variability, etc. Moreover, there are many unknown and unexpected factors that will affect the disaster response strategy. But, the future Crisis Management Systems is needed that past disaster teaching. In another words, from now on the response systems need to prepare several scenarios and spatial data and manual etc. before the disaster. Then, this research is the experimental research which examined the relationship between the disaster-ethnography and the GIS spatial data of disaster.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.65-72
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• 2001

With the recent rising project complexities and competitive environments in the construction projects, a risk management is recognized as more important management tool than the others. However, as most risk management techniques applied to the construction projects are centered around their initial phases and risk analyses, they are not developed into general project management technique such as time management, cost management and quality management, etc., that are usually applied in the process of construction. Thus, this paper proposes a response process to construction project risks based on the risk threshold and its calculation methodology applying a concept of VaR to establish risk management as general management technique in the construction projects.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.158-163
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• 2013

While job stress evaluations are reported in the recent surveys upon the nuclear power plants(NPPs), any significant advance in the types of questionnaires is not currently found. There are limitations to their usefulness as analytic tools for the management of safety resources in NPPs. Data mining(DM) has emerged as one of the key features for data computing and analysis to conduct a survey analysis. There are still limitations to its capability such as dimensionality associated with many survey questions and quality of information. Even though some survey methods may have significant advantages, often these methods do not provide enough evidence of causal relationships and the statistical inferences among a large number of input factors and responses. In order to address these limitations on the data computing and analysis capabilities, we propose an advanced procedure of survey analysis incorporating the DM method into a statistical analysis. The DM method can reduce dimensionality of risk factors, but DM method may not discuss the robustness of solutions, either by considering data preprocesses for outliers and missing values, or by considering uncontrollable noise factors. We propose three steps to address these limitations. The first step shows data mining with response surface method(RSM), to deal with specific situations by creating a new method called response surface data mining(RSDM). The second step follows the RSDM with detailed statistical relationships between the risk factors and the response of interest, and shows the demonstration the proposed RSDM can effectively find significant physical, psycho-social, and environmental risk factors by reducing the dimensionality with the process providing detailed statistical inferences. The final step suggest a robust stress management system which effectively manage job stress of the workers in NPPs as a part of a safety resource management using the surrogate variable concept.

• 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.