Cumulative correspondence analysis of ordered categorical data from industrial experiments


D'AMBRA L., Koksoy O. , SIMONETTI B.

JOURNAL OF APPLIED STATISTICS, cilt.36, ss.1315-1328, 2009 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 36 Konu: 12
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1080/02664760802638090
  • Dergi Adı: JOURNAL OF APPLIED STATISTICS
  • Sayfa Sayıları: ss.1315-1328

Özet

Most studies of quality improvement deal with ordered categorical data from industrial experiments. Accounting for the ordering of such data plays an important role in effectively determining the optimal factor level of combination. This paper utilizes the correspondence analysis to develop a procedure to improve the ordered categorical response in a multifactor state system based on Taguchi's statistic. Users may find the proposed procedure in this paper to be attractive because we suggest a simple and also popular statistical tool for graphically identifying the really important factors and determining 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.