Developing statistical models in an early warning system and its empirical study

Pei-Nong Chen, Chen-Fu Chien, Sheng-Jen Wang, Chien-chung Chen, Haw-Jyue Luo
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Abstract

When a new equipment or process is released, it is critical to ensure it behave as expected and stay in normal condition. The study proposes a research framework in which a statistical model is constructed for newly released equipment and process monitoring. An empirical study is conducted in a DRAM fabrication facility for validation. Based on the model, a best set of sample test items which discriminates the newly released equipment is selected and a group of normal equipments is obtained. Thus, the alarm signals can be triggered in an early warning system.
预警系统统计模型的建立及其实证研究
当新设备或新工艺发布时,确保其按预期运行并保持正常状态是至关重要的。本研究提出了一种研究框架,在该框架中构建了新出厂设备和过程监测的统计模型。并在一家DRAM制造工厂进行了实证研究。在此模型的基础上,选取了一组最优的样本测试项目来判别新发布的设备,得到了一组正常的设备。因此,预警系统可以触发报警信号。
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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