• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.109-114
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• 1997

As CNC machine tool is one of core elements of manufacturing system, it is much important that it remains without troubleshoots. As a virtual machine is a recent alternative using IT for optimal utilization of CNC machine tool, it is a computer model that represents a CNC machine tool. But a virtual machine is still conceptual. So, in this paper, it is proposed that a virtual machine be a realistic model in the fault diagnosis module. For this purpose, the fault diagnosis system of machine tool using CORBA and fault diagnosis expert system has been implemented. Using this system, we have expections to diagnose exactly and prompty without the restriction of time or location, to reduce MTTR(Mean Time To Repair) and finally to increase the availability of manufacturing system.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 2000년도 제17회 하계학술발표회 논문집
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• pp.65-83
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• 2000

In this study, we propose an expert system aided model necessary for extracting the rules, which can diagnose the success level of new product development project. For this purpose, first, we design a classification model to analyze the characteristics of $\ulcorner$parts development projects$\lrcorner$. Second, in order to select success factors, we explore literatures and interview with project managers working at large sized companies of electronic parts. And we conduct the enquete survey and statistical analysis to extract key success factors. Third, in order to decide the level of project success, we use the concept of 'Recearchitivity' as a framework of judgement criteria. Fourth, in order to extract diagnosis rules, we use expert system development tool.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.439-443
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• 1996

A fuzzy teaming controller is experimentally designed to control the ball k beam system in this paper. Although most fuzzy controllers have been built just to emulate human decision-making behavior, it is necessary to construct the rule bases by using a learning method with self-improvement when it is difficult or impossible to get them only by expert's experience. The algorithm introduces a reference model to generate a desired output and minimizes a performance index function based on the error and error-rate using the gradient-decent method. In our balancing experiment of the ball ＆ beam system, this paper shows that the fuzzy control rules by learning are superior to the expert's experience.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2005년도 학술발표논문집
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• pp.527-533
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• 2005

Recently reservoir is polluted by concentrative development of urbanization. Accordingly, the prediction of water quality has import meaning for protecting of water quality pollution. This study was carried out to predict water quality of Gyung Cheon reservoir by WASP5. We have established an integrated system on the basis of web, which predicts the future quality of water through water quality model, WASP5 based on information of water environment in a reservoir for agriculture, uniting expert system which supports the determination to set up measures for improving the quality of water to cope with the result.

• Journal of Advanced Marine Engineering and Technology
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• 제23권5호
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• pp.622-629
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• 1999

This paper presents the development of an interactive knowledge-based CAM system for design-ing and manufacturing the mold. The system is composed of two functional parts. One is the geo-metric modeller that uses the feature-based models. The models include base plate step, hole, pocket, boss and slot, These are designed by interactive user interface. The other is the expert sys-tem module with inference engine and knowledge database of workpiece material tools manufac-turing machines process an working conditions. With two parts the final mold shape is generated with manufacturing information for effective production.

• 대한산업공학회지
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• 제14권2호
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• pp.53-61
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• 1988

Games such as baseball, soccer are scheduled by a given game type such as tournament, league or their mixed form. The objective of this paper is to find an efficient game-scheduling method with respect to traveling distance, break-time and other conditions. In this paper we first present two models which minimize traveling distance. The first model that a match is played once each other is solved by a heuristic method. In the second model that a match is played more than once, teams are paired by a modified 0 - 1 programming, and the pairs are rearranged in order to generate a number of workable schedules. Then Expert Systems is applied to solve breake-time and other conditions. In order to represent expertise's knowledge effectively, we present a new design of knowledge-base and data-base, inference engine including many rules and meta-rules which controls the global system. In knowledge-base, binary relation among various attributes is used to ease not only knowledge acquisition but also system execution.

• 지능정보연구
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• 제1권2호
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• pp.1-16
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• 1995

The field of human judgment and decision making provides useful methodologies for examining the human decision making process and substantive results. One of the methodologies is a lens model analysis which can examine valid nonlinearity in the human decision making process. Using the method, valid nonlinearity in human decision behavior can be successfully detected. Two linear(statistical) models of human experts and two nonlinear models of human experts are compared in terms of predictive accuracy (predictive validity). The results indicate that nonlinear models can capture factors(valid nonlinearity) that contribute to the expert's predictive accuracy, but not factors (inconsistency) that detract from their predictive accuracy. Then, it is argued that nonlinear models cab be more accurate than linear models, or as accurate as human experts, especially when human experts employ valid nonlinear strategies in decision making.

• 한국정밀공학회지
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• 제13권3호
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• pp.102-109
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• 1996

In this paper, we present a new approach for the automation of deburring process. An algorithm for teaching skills of a human expert to a robot manipulator is developed. This approach makes use of TSK fuzzy mode that can wxpress a highly nonlinear functional relation with small number of rules. Burr features such as height, width, area, grinding area are extracted from image processing by use of the vision system. Grinding depth, repetitive number and normal grinding force are chosen as control signals representing actions of the human expert. It is verified that our proposed fuzzy model can accurately express the skills of human experts for the deburring process.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1165-1168
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• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.

• 산업공학
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• 제16권1호
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• pp.103-110
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• 2003

Growth curves are widely used in forecasting the market demand. When there are only a few data points available, the estimated model parameters have a low confidence. In this case, if some expert opinions are available, it would be better for predicting future demand to adjust the model parameters using these information. This paper proposes the methodology for re-estimation of model parameters in growth curves when adjusting market potential and/or time of maximum sales. We also provide the detailed procedures for five growth curves including Bass, Logistic, Gompertz, Weibull and Cumulative Lognormal models. Applications to real data are also included.