Intelligent manufacturing system design and its adaptation to electronic commerce : semiconductor adaptive sampling system based on data mining and intelligent agent = 지능형 제조시스템 설계 및 전자상거래에의 적용 : 데이터 마이닝과 지능형 에이전트 기반 반도체 순응형 샘플링 시스템semiconductor adaptive sampling system based on data mining and intelligent agent

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The commercialization and privatization of the Internet and its successive increase in popularity a few years ago are the foundations that began to propel the growth in Electronic Commerce (e-Commerce). As companies migrate toward responsive e-Commerce models, they need an effective manufacturing system that allows them to react rapidly and continuously, innovate ceaselessly, and move fast and quickly adapt to change in order to deal with dynamic change of marketplace and customer needs. This thesis proposes the use of intelligent manufacturing system (IMS) for that objective, and presents an intelligent decision support system (IDSS) based on data mining and agent technologies for an optimal sampling method decision in semiconductor manufacturing process as a pilot study in the IMS design. This thesis also presents its adaptation to the semiconductor e-Commerce model. IDSSs, incorporating intelligent agent and data mining, are designed to aid the decision-making by taking advantages of those technologies. Data mining technology provides an important contribution to the IDSSs by providing techniques which decision support systems (DSSs) are able to utilize in providing a wide range of information available for decision-makers, and intelligent agent technology offers the intelligent, autonomous, active and co-operative nature to the DSSs. This thesis presents an IDSS, called adaptive sampling system (ASS), for the autonomous decision of an optimal sampling method in semiconductor manufacturing process. ASS has an intelligent agent-based novel architecture that takes advantage of the intelligent, autonomous, and active aspects of intelligent agent technology. And also, it has a successful integration of data mining technology for the optimal sampling decision into a DSS framework by means of applying intelligent agent technology. We design the ASS having a methodology how to generate an optimal static sampling method and the associated decision process based on...
Park, Sang-Chan박상찬
한국과학기술원 : 산업공학과,
Issue Date
169522/325007 / 000985275

학위논문(박사) - 한국과학기술원 : 산업공학과, 2001.8, [ ix, 149 p. ]


sampling; semiconductor; electronic commerce; manufacturing; intelligent decision support system; 전자상거래; 샘플링; 반도체; 지능형 의사결정지원시스템; 제조시스템

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