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

Caterina Rizzo (Corresponding author), Alessandro Di Bucchianico

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6 Citaten (Scopus)
141 Downloads (Pure)

Samenvatting

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.

Originele taal-2Engels
Pagina's (van-tot)523-531
Aantal pagina's9
TijdschriftQuality and Reliability Engineering International
Volume39
Nummer van het tijdschrift2
DOI's
StatusGepubliceerd - mrt. 2023

Bibliografische nota

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.

Financiering

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.

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