<title>Data-driven method for calculating limits for particle control charts</title>

Abstract

In semiconductor manufacturing, a key measure of product quality is the number of particles added during a fab processing step. Usual statistical process control methods assume an underlying normal distribution for the data. Particle measurements typically display skewed, nonnormal distributions, hence traditional control limits are not valid. This paper examines using bootstrap estimates ofthe upper percentiles of a distribution to find control limits for particle charts.