Improved yield estimation with efficient decision power for multi-line processes

Abstract

Portable devices with multiple functions are commonly used in modern life, and the dies in these products have become much thinner and slimmer over time. Due to the rapid advancements in manufacturing technology in the semi-conductor industry, the process yield requirements grow increasingly strict. In advanced packaging manufacturing, the process is usually with multiple lines and often requires a very low fraction of defective. To assess the manufacturing yield precisely, the process capability index is widely used. is a generalization yield index designated for measuring the yield of multi-line processes. However, the typical existing method for obtaining the lower confidence bound of is conservative and it may mislead managers into making incorrect decisions. In this study, the nonparametric and parametric standard bootstrap methods have been implemented to establish a reliable and improved yield assessment. Three methods are investigated and the power comparison is provided. Then, two effective transformation methods to handle non-normal processes are presented and one example with simulation data is given for algorithm demonstration. Finally, an application of yield assessment for underfill processes with two manufacturing lines is presented. The simulation results demonstrate that based on the proposed method, we can reliably evaluate the true manufacturing yield and make a more powerful decision.