• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.28
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• pp.59-67
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• 1993

Recently, The concept of strategic groups is recognized as a basic unit of understanding framework in strategic management research. Researchers have consistently approached the relationship between strategic groups and organizational variables(organization structure vs strategies, management process vs strategies, management systems vs strategies, environment vs strategies, strategies vs performance). However the relationship between strategic groups and human resources has been neglected in theortical approach and empirical approach. Therefore this study explores the relationship between strategic groups and human resources management.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.4
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• pp.29-38
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• 2003

This paper deals with an automated computer-aided process planning and die design system with which designer can determine operation sequences even after only a little experience in process planning and die design of multi former-bolt products by multi-stage former working. The approach is based on knowledge-based rules, and a process knowledge base consisting of design rules is built. Knowledge fur the system is formulated from plasticity theories, empirical results and the empirical knowledge of field experts. Programs for the system have been written in AutoLISP for AutoCAD with a personal computer. An attempt is made to link programs incorporating a number of expert design rules with the process variables obtained by commercial FEM softwares, DEFORM and ANSYS, to form a useful package. The system is composed of four main modules. The process planning and die design module considers several factors, such as the complexities of preform geometry, punch and die profiles, specifications of available multi former, and the availability of standard parts. It can provide a flexible process based on either the reduction in the number of forming sequences by combining the possible two processes in sequence, or the reduction of deviation of the distribution and the level of the required forming loads by controlling the forming ratios. The system uses 2D geometry recognition and is integrated with the technology of process planning, die design, and CAE analysis. The standardization of die parts for multi former-bolt products requiring a cold forging process is described. The system developed makes it possible to design and manufacture multi former-bolt products more efficiently.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.107-118
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• 2002

This paper deals with an automated computer-aided process planning and die design system by which designer can determine operation sequences even if they have a little experience in process planning and die design of quasi-axisymmetric cold forging product by cold former working. The approach to the system is based on knowledge-based rules and a process knowledge base consisting of design rules is built. Knowledge for the system is formulated from plasticity theories, empirical results and the empirical knowledge of field experts. Programs for the system have been written in AutoLISP for the AutoCAD using a personal computer. An attempt is made to link programs incorporating a number of expert design rules with the process variables obtained by commercial FEM softwares, DEFORM and ANSYS, to form a useful package. The system is composed of three main modules and five sub-modules. The process planning and die design module considers several factors, such as the complexities of preform geometry, punch and die profiles, specifications of available cold farmer, and the availability of standard parts. As the system using 2D geometry recognition is integrated with the technology of process planning, die design, and CAE analysis, the standardization of die parts for wheel bolt requiring cold forging process is possible. The developed system makes it possible to design and manufacture quasi-axisymmetric cold forging product more efficiently.

• 한국디지털정책학회:학술대회논문집
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• 2004.05a
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• pp.151-165
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• 2004

In this paper we would like to provide a help to implementing KMS(Knowledge Management System) in public sector. For this purpose, we set up five contingency environmental factors and three process factors of knowledge management. And then investigates affecting factors effect on the performance of KMS in public sector by empirical study. A field survey of public officers in Korea local government was conducted. Complete data for 333 KMS users was analyzed to determine relationship of the research constructs. The system of evaluation and compensation is the most important factor effects on the process of KM and the performance of KMS. These results provide empirical evidence that supports the necessity of rational motivation systems does lead to effective implementation of KMS in public sector.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.4
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• pp.69-78
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• 2002

The basic purpose of the JIT(Just In Time) production system is to increase profits by reducing costs-that is, by completely eliminating waste such as excessive stocks or workforce. To achieve cost reduction, Production must promptly and flexibly adapt to changes in market demand without having wasteful slacks. :iuch an ideal is accomplished by the concept of JIT, producing the necessary items in the necessary quantities at the necessary time. The JIT production system is supported by the following: reduction of setup time, smoothing of production, standardization of jobs, improvement activities, design of machine layout, Kanban system, autonomation etc. This study examined the present state of the domestic JIT production system and introduced the empirical case of JIT application a small and medium manufacturing company. A synthetic resins manufacturing company applied JIT principles to its processes and achieved the great performance.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.885-898
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• 2012

In this paper, we consider Bayesian approaches to partially linear models, in which a regression function is represented by a semiparametric additive form of a parametric linear regression function and a nonparametric regression function. We make a comparative study on the performance of widely used Bayesian partially linear models in terms of empirical analysis. Specifically, we deal with three Bayesian methods to estimate the nonparametric regression function, one method using Fourier series representation, the other method based on Gaussian process regression approach, and the third method based on the smoothness of the function and differencing. We compare the numerical performance of three methods by the root mean squared error(RMSE). For empirical analysis, we consider synthetic data with simulation studies and real data application by fitting each of them with three Bayesian methods and comparing the RMSEs.

• Journal of Digital Convergence
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• v.2 no.1
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• pp.113-126
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• 2004

In this paper we would like to provide a help to implementing KMS(Knowledge Management System) in public sector. For this purpose, we set up five contingency environmental factors and three process factors of knowledge management. And then investigates affecting factors effect on the performance of KMS in public sector by empirical study, A field survey of public officers in Korea local government was conducted. Complete data for 333 KMS users was analyzed to determine relationship of the research constructs. The system of evaluation and compensation is the most important factor effects on the process of KM and the performance of KMS. These results provide empirical evidence that supports the necessity of rational motivation systems does lead to effective implementation of KMS in public sector.

• Management & Information Systems Review
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• v.22
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• pp.1-23
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• 2007

This paper investigates the relationships between exports, firm size, and firm dynamics. It is based on a longitudinal data covering listed firms in the Korean manufacturing industry. We found the stylized fact that the probability that a firm is exporter increases with firm size. A regression model for the determinant of export/sales ratio including dynamic adjustment process is tested on a cross-section sample for the year 2001. Empirical findings suggest that there is a positive and inversely U-shaped relationship between firm size and export/sales ratio, just for basic material and capital good industry. Except for firm size, the hypotheses concerning human capital intensity, physical capital intensity, R&D intensity, and patent are rejected. Using Granger causality test, we found that the rate of growth of total sales influences the change of the export/sales ratio with time lag for medium-sized firms. Finally, some policy implications are presented.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.163-175
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• 2020

We consider a wide class of general weakly-dependent processes, called ψ-weak dependence, which unify almost all weak dependence structures of interest found in statistics under natural conditions on process parameters, such as mixing, association, Bernoulli shifts, and Markovian sequences. For detecting the tail behavior of the weakly dependent processes, change point tests are developed by means of cumulative sum (CUSUM) statistics with the empirical distribution functions of sample extremes. The null limiting distribution is established as a Brownian bridge. Its proof is based on the ψ-weak dependence structure and the existence of the phantom distribution function of stationary weakly-dependent processes. A Monte-Carlo study is conducted to see the performance of sizes and powers of the CUSUM tests in GARCH(1, 1) models; in addition, real data applications are given with log-returns of financial data such as the Korean stock price index.

• Journal of Korean Society for Quality Management
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• v.8 no.1
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• pp.3-7
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• 1980

In many industrial processes, there are more than two responses (i.e., yield, percent impurity, etc.) of interest, and it is desirable to determine the optimal levels of the factors (i.e., temperature, pressure, etc.) that influence the responses. Suppose the response relationships are assumed to be approximated by second-order polynomial regression models. The problems considered in this paper is, first, to propose how to select polynomial terms to fit the multivariate regression surfaces for a given set of data, and, second, to propose how to analyze the data to obtain an optimal operating condition for the factors. The proposed techniques were applied for empirical process optimization in a tire company in Korea. This case is presented as an illustration.