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The Application of Data Mining Technology for Intelligent Product Quality Analysis Improvement System

机译：数据挖掘技术在智能产品质量分析改进系统中的应用

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摘要

This paper illustrates the design and construction of such an environment, called intelligent product quality analysis improvement system involved in using data warehouse, OLAP and data mining technologies to discover the main significant reasons in the manufacturing process of packaging plants and compare the accurate classification analysis of the two methods, i.e. decision tree and neural network, so as to set up a system providing an efficiency tool for analyzing problems, with a view to identifying the causes of problems, making decision immediately, and eventually reducing the cycle time taken to solve quality-related problems. The experimental results of this research show that the predictions made by decision tree analysis are more accurate than those made by neural network. Eventually, we take advantage of decision tree method to reduce the defected chips, increases the production yields in the packaging industry.
机译：本文说明了这种环境的设计和构建，该环境称为智能产品质量分析改进系统，涉及使用数据仓库，OLAP和数据挖掘技术来发现包装工厂制造过程中的主要重要原因，并比较包装的精确分类分析。两种方法，即决策树和神经网络，以建立一个提供用于分析问题的效率工具的系统，以识别问题的原因，立即做出决定并最终减少解决质量所花费的时间相关的问题。这项研究的实验结果表明，决策树分析做出的预测比神经网络做出的预测更准确。最终，我们利用决策树方法减少了缺陷芯片，提高了包装行业的产量。

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