Generalized likelihood ratio control charts for high-purity (high-quality) processes

Caterina Rizzo (Corresponding author), Alessandro Di Bucchianico

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
76 Downloads (Pure)


Generalized likelihood ratio (GLR) control charts are useful for tailor-made monitoring strategies, but they are less developed for discrete processes. In this paper, the GLR control chart framework applied to aggregate cumulative quantities data is extended. Inspired by the technical note on GLR control charts from Lee and Woodall (2018), unnecessary artificial bounds in the GLR chart for geometric data proposed in literature are removed and parameter restriction errors, common in GLR designs, are corrected. Finally, the Gamma GLR chart for continuous-time time-between-event data that can be modeled by a Poisson process is proposed and its performance are evaluated and compared to its traditional competitors.

Original languageEnglish
Pages (from-to)523-531
Number of pages9
JournalQuality and Reliability Engineering International
Issue number2
Publication statusPublished - Mar 2023

Bibliographical note

Funding Information:
The authors thank the reviewers for the comments and suggestions that improved the paper. The suggestions of future work in the conclusion section originated from the insightful comments by the reviewers. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.


  • GLR control chart
  • high-purity processes
  • high-quality processes
  • time-between-events control chart


Dive into the research topics of 'Generalized likelihood ratio control charts for high-purity (high-quality) processes'. Together they form a unique fingerprint.

Cite this