A new defect distribution metrology with a consistent discrete exponential formula and its applications

Abstract

We have proposed a novel discrete exponential distribution function, which describes a defect count distribution on wafers or chips more accurately, especially in near defect-free conditions. The conventional approach based on a gamma probability density function (g-pdf) is known to fail in expressing the defects of defect-free wafers or chips, because it always gives zero as the pdf value. Since the number of defects is countable (discrete distribution should be used) and analyzed in terms of nondefective chip yield, the g-pdf cannot be used because of its inaccuracy in the near defect-free condition. A discrete exponential pdf is introduced corresponding to the defect count distribution. In addition, a convolution formula of the new pdf is derived statistically which can express realistic defect count distribution with multiple defect sources. It is noted that the popular negative binomial yield formula (NBYF) is directly derived with the convoluted discrete exponential distribution, which interprets the cluster factor given in NBYF as the number of different defect sources predicted. It is experimentally proven that defect count distributions are approximated by this new model within an average error of about 0.01 defects per wafer from film deposition process data.