• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1-5
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• 2005

The grinding process is replacing lapping and etching process because significant cost savings and performance improvemnets is possible. This paper presents the experimental results of wafer grinding. A three-variable two-level full factorial design was employed to reveal the main effects as well as the interaction effects of three process parameters such as wheel rotational speed, chuck table rotational speed and feed rate on TTV and STIR of wafers. The chuck table rotaional speed was a significant factor and the interaction effects was significant. The ground wafer shape was affected by surface shape of chuck table.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.563-564
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• 2006

In silicon wafer manufacturing process, the grinding process has been adopted to improve the flatness of water. The grinding of wafer is usually used by the infeed grinding machine. Grinding conditions are spindle speed, feed speed, rotation speed, grinding stone etc. But grinding condition selection and analysis is so difficult in grinding machine. In the intelligent grinding system based on knowledge many researchers have studied expert system, neural network, fuzzy etc. In this paper we deal grinding condition selection method, Taguchi method and Genetic Analysis.