Group selection for processes with multiple quality characteristics

Chen Ju Lin*, W.l. Pearn, J. Y. Huang, Y. H. Chen

*Corresponding author for this work

Research output: Contribution to journalArticle

5 Scopus citations


Evaluating and comparing process capabilities are important tasks of production management. Manufacturers should apply the process with the highest capability among competing processes. A process group selection method is developed to solve the process selection problem based on overall yields. The goal is to select the processes with the highest overall yield among I processes under multiple quality characteristics, I > 2. The proposed method uses Bonferroni adjustment to control the overall error rate of comparing multiple processes. The critical values and the required sample sizes for designated powers are provided for practical use.

Original languageEnglish
Pages (from-to)3923-3934
Number of pages12
JournalCommunications in Statistics - Theory and Methods
Issue number16
StatePublished - 18 Aug 2018


  • Bonferroni adjustment
  • Process capability
  • Process selection

Fingerprint Dive into the research topics of 'Group selection for processes with multiple quality characteristics'. Together they form a unique fingerprint.

Cite this