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Big Data and Predictive Analytics Methods for Modeling and Analysis of Semiconductor Manufacturing Processes

机译:用于半导体制造过程建模和分析的大数据和预测分析方法

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Semiconductor manufacturing fabs generate huge amount of data. The big data approaches of data management have increased speed, quality and accessibility of the data. This paper discusses harnessing value from this data using predictive analytics methods. Various aspects predictive analytics in the context of semiconductor manufacturing are discussed. The limitations of standard methods of analysis and the need to adopt robust methods of modeling and analysis are highlighted. The robust prediction modeling method is implemented on wafer sensor data resulting in improved prediction ability of wafer quality characteristics.
机译:半导体制造厂会产生大量数据。数据管理的大数据方法提高了数据的速度,质量和可访问性。本文讨论了使用预测分析方法从这些数据中挖掘价值的方法。讨论了半导体制造方面的预测分析的各个方面。强调了标准分析方法的局限性以及采用可靠的建模和分析方法的需求。对晶片传感器数据实施鲁棒的预测建模方法,从而提高了晶片质量特性的预测能力。

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