Cumulative correspondence analysis for identifying optimal level of factors . A case study for optimizing the polysilicon deposition process.

Industrial quality characteristics are often measured categorically rather then numerically and sometimes we have ordered categorical dates. Accounting for the ordering of such data plays an important role in determining effectively the optimal factor level of combination. This paper utilizes correspondence analysis to develop a procedure for improving the ordered categorical response in a multifactor state system based on the Taguchi’s statistic. Users may find the proposed procedure in this article to be attractive because we suggest a simple and also popular statistical tool for graphically identifying the really important factors and determine the levels to improve process quality. A case study for optimizing the polysilicon deposition process in a very large-scale integrated circuit is provided to demonstrate the effectiveness of the proposed procedure. The results are compared with other approaches proposed in literature.