Improving yield in IC manufacturing by statistical analysis of a large database

摘要

Data analysis is the third pillar of statistical quality control beside control charts and design of experiment; it reveals the link between process and test variables. Important benefits can be achieved by using well-known analytical methods— that is, the statistical analysis of data from databases. An investigation of problems that arose at the Motorola IC fab in Toulouse, France, demonstrated that data analysis methods are very useful for quality and yield improvement. That research involves all the statistical methods of analyzing data from databases, including those not covered by control charts and design of experiments (DOE). Analysis of variance, nonpara-metric tests, multiple regression, and generalized linear models were found to be efficient methods for confronting concrete problems such as the nonnor-mal distribution of electrical tests.