Challenges Associated with Realization of Lot Level Fab Out Forecast in a Giga Wafer Fabrication Plant

Georg Seidel, Ching Foong Lee, Aik Ying Tang, Soo Leen Low, Boon-Ping Gan, W. Scholl
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Abstract

In the semiconductor industry a reliable delivery forecast is helpful to optimize demand planning. Very often cycle time estimations for frontend, backend production, testing and transits are used to predict delivery times on product level and to determine when products have to be started to fulfill customer demands on time. Frontend production usually consumes a big portion of the cycle time of a product. Therefore a reliable cycle time estimation for a frontend production is crucial for the accuracy of the overall cycle time prediction. We compare two different methods to predict cycle times and delivery forecasts on product and lot level for a frontend production: a Big Data approach, where historical data is analyzed to predict future behavior, and a fab simulation model.
实现千兆晶圆厂批量级晶圆缺货预测所面临的挑战
在半导体行业,可靠的交货预测有助于优化需求规划。通常,前端、后端生产、测试和中转的周期时间估计用于预测产品级别的交付时间,并确定何时必须开始生产产品以按时满足客户需求。前端生产通常消耗产品周期时间的很大一部分。因此,对前端生产进行可靠的周期时间估计对于整个周期时间预测的准确性至关重要。我们比较了两种不同的方法来预测前端生产的周期时间和交货预测:一种是大数据方法,通过分析历史数据来预测未来的行为,另一种是晶圆厂模拟模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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