Monitoring and diagnostic techniques for control of overlay in steppers

Abstract

Semiconductor lithography manufacturing presents a major challenge for the application of classical Statistical Process Control (SPC) methodologies due to the complex nature of this process. For example, difficulties can occur due to inadequate data sampling, nonnormal error distributions, equipment or process instability and nonstationary random errors. Incorrect use of classical SPC techniques can result in the incorrect interpretation of process stability which can have a drastic impact on productivity. Photolithography provides additional SPC challenges due to the inherent multivariable nature of the output variables that are being controlled. This paper examines appropriate SPC and monitoring techniques for stepper control of overlay performance using in-process measurement and analysis equipment to address these issues. The average run length of three charting techniques is compared to quantify the ability of each technique to detect process mean shifts. Shewart, Exponentially Weighted Moving-Average (EWMA) and Cumulative-Sum (CUSUM) charts are analyzed for a baseline process and mean shifts of 0.42, 0.85 and 1.25 standard deviations. These results illustrate the superior performance of a CUSUM chart over Shewart and EWMA charts. In addition, the Shewart chart with Western Electric rules produced false mean shift alarms for the baseline case. The EWMA is also observed to be sensitive to the selection of weighting factors. The effectiveness of plotting individual wafers is compared with plotting lot means. The plotting of individual wafers outperforms lot means in the determination of baseline shifts because of the larger population size of the individual charts.