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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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🏛️國立陽明交通大學機構典藏

Subject: search.filters.subject.computer integrated manufacturing (CIM)

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Now showing 1 - 3 of 3
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    Item type:Item,
    Design an intelligent CIM system based on data mining technology for new manufacturing processes
    (2004)
    Wu, RC
    ;
    Chen, RS
    ;
    Fan, CR
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    The purpose of this paper is to explain a specific intelligent CIM (computer integrated manufacturing) system by integrating the following five major subject areas: computer integrated manufacturing, data warehouse, online analytical processing (OLAP), data mining and artificial intelligence. The data mining system makes use of the decision tree algorithm and classification model in exploring the meaningful information, which is useful in the process of decision making. Subsequently, the rules discovered by the data mining system are expressed through the rule based knowledge presentation method of the expert system. The intelligent CIM system is applied to semiconductor packing factories and also point at the great fluctuation of DRAM (dynamic random access memory) prices. The results of this paper are the product yield, the manufacturing cycle time and the frequency of holding lot, which have been improved. The contribution can increase business competitiveness, reduce production cost, and promote the rate of available promise for order.
  • Thumbnail Image
    Item type:Item,
    Using data mining technology to design an intelligent CIM system for IC manufacturing
    (2005)
    Chen, RS
    ;
    Wu, RC
    ;
    Chang, CC
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    This paper aims to explain a specific intelligent computer integrated manufacturing system by integrating the following five major domains: computer integrated manufacturing, data warehouse, online analytical processing, data mining and artificial intelligence. The data mining system makes use of the decision tree algorithm and classification model in exploring the meaningful information, which is useful in the process of decision making. Subsequently, the rules discovered by the data mining system are expressed through the rule based knowledge presentation method of the expert system. The intelligent CIM system is applied to semiconductor packing factories and also point at the great fluctuation of dynamic random access memory prices. The contribution can increase business competitiveness, reduce production cost, and promote the rate Of available promise for order.
  • Thumbnail Image
    Item type:Item,
    Using Bayesian networks to build data mining applications for a semiconductor cleaning process
    (2007)
    Chen, Ruey-Shun
    ;
    Chang, Chan-Chine
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    Data mining is part of the knowledge discovery process that offers a new way to look at data. It consists of the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. It is the discovery of patterns that lie hidden among a set of data. A Bayesian networks is a specific model of knowledge network. It offers useful information about the mutual dependencies among the features in the application domain. Such information can be used for gaining better understanding about the dynamics of the process under observation. Manufacturing process monitoring using Bayesian networks is a quite useful example. In this paper, we provide Bayesian networks to extract knowledge from data. We present an approach for the Bayesian networks to implement a data mining task for computer integrated manufacturing (CIM). It could find the cause factors in various parameters that affect in semiconductor cleaning process.