• Computers and Concrete
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• v.14 no.4
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• pp.445-462
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• 2014

To solve structural optimization problems, it is necessary to integrate a structural analysis package and an optimization package. There have been many packages that can be employed to analyze reinforced concrete plane frames. However, because most structural analysis packages suffer from closeness of systems, it is very difficult to integrate them with optimization packages. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrates Design, Analysis, Modeling, Definition, and Optimization phases into an integration environment as follows. (1) Design: first generate many possible structural design alternatives. Each design alternative consists of many design variables X. (2) Analysis: employ the structural analysis software to analyze all structural design alternatives to obtain their internal forces and displacements. They are the response variables Y. (3) Modeling: employ artificial neural networks to build the models Y=f(X) to obtain the relationship functions between the design variables X and the response variables Y. (4) Definition: employ the design variables X and the response variables Y to define the objective function and constraint functions. (5) Optimization: employ the optimization software to solve the optimization problem consisting of the objective function and the constraint functions to produce the optimum design variables. The RC frame optimization problem was examined to evaluate the DAMDO approach, and the empirical results showed that it can be solved by the approach.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.330-333
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• 2006

Many practical problems of quality control in service management are derived from the use of ordinal variables. Ordered linguistic variables differ from measurement variables. This paper presents a new control chart of a production process based on ordinal variables.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.990-997
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• 2005

Many products, such as gasoline, polymer plastics, alloys, and ceramics are manufactured by mixing two or more ingredients or components. When we are to develop new mixture products, we must deal with a long list of potentially important component variables. This paper introduces some design methods for many mixture variables and some analysis tools for screening important variables out of the many candidate variables. The results of this paper will be helpful to engineers who work in the research and development sector of chemical, polymer, alloys, and electro-material industries.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.513-516
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• 2004

Evolutionary operation is useful to improve on-line full-scale manufacturing processes by systematically changing the levels of the process variables while meeting production schedule. Evolutionary operation was developed using two or three process variables for process operators who are not good at statistics. Recently, when a product is developed, it is very important for the engineers to make the production line stable as soon as possible. And there are many causes which have influences to the product performance. This paper presents an evolutionary operation procedure with many process variables using saturated two level fractional factorial designs including Plackett-Burman design.

• Bulletin of the Korean Mathematical Society
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• v.45 no.2
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• pp.339-353
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• 2008

The distributions of products and ratios of random variables are of interest in many areas of the sciences. In this paper, the exact distributions of the product |XY| and the ratio |X/Y| are derived when X and Y are independent Pearson type VII random variables.

• Bulletin of the Korean Chemical Society
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• v.20 no.5
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• pp.525-527
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• 1999

Many types of chemical data tend to be characterized by many measured variables on each of a few observations. In this situation, target concentration can be predicted using multivariate statistical modeling. However, it is necessary to use a few variables considering size and cost of instrumentation, for an example, for development of a portable biomedical instrument. This study presents, with a spectral data set of total hemoglobin in whole blood, the possibility that modeling using only a few variables can improve predictability compared to modeling using all of the variables. Predictability from the model using three wavelengths selected from all possible regression method was improved, compared to the model using whole spectra (whole spectra: SEP = 0.4 g/dL, 3-wavelengths: SEP=0.3 g/dL). It appears that the proper selection of variables can be more effective than using whole spectra for determining the hemoglobin concentration in whole blood.

• Kyungpook Mathematical Journal
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• v.31 no.2
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• pp.185-191
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• 1991

• Journal of Korean Society for Quality Management
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• v.34 no.2
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• pp.129-135
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• 2006

In the advance of computer technology, it is possible to keep all the related informations for monitoring equipments in control and huge amount of real time manufacturing data in a data base. Thus, the statistical analysis of large data sets with hundreds of thousands observations and hundred of independent variables whose some of values are missing at many observations is needed even though it is a formidable computational task. A tree structured approach to classification is capable of screening important independent variables and their interactions. In a Six Sigma project handling large amount of manufacturing data, one of the goals is to screen vital few variables among trivial many variables. In this paper we have reviewed and summarized CART, C4.5 and CHAID algorithms and proposed a simple method of screening vital few variables by selecting common variables screened by all the three algorithms. Also how to develop a logistics regression model on a large data set is discussed and illustrated through a large finance data set collected by a credit bureau for th purpose of predicting the bankruptcy of the company.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.59-73
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• 2000

Nowadays many People know well that happiness depends not on richness but on health and wellbeing, and many researchers have studied about such subjects. This paper studies correlations, causal relations and factors of many variables to be considered to be able to explain human health and welfare in a country system, using Kendall's tau and factor analysis methods. Also it finds what main variables are to be controlled for a country system to become more advanced in various sides of health and welfare, using Mann-Whitney statistics. The contribution of this paper is that it can suggest essential variables and important relations which are helpful to construct an efficient system of health and welfare in Korea.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.147-150
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• 1996

A homing torpedo's performance can be expressed a function of many variables, i.e. technical and tactical variables. When designing a homing torpedo, these variables have to be decided upon. The system effectiveness of a homing torpedo can be determined by analyzing of these variables. This paper describes a procedure of simulation metamodelling using a Factor Analysis methodology. A simulation model was used in order to obtain the data base for analyzing detection probability of torpedo. By analyzing the main and interaction effects these variables on the analysis of detection probability, we will show the importance of certain variables, of a homing torpedo.