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001-es BibID:	BIBFORM121325
035-os BibID:	(WOS)000765783100001
Első szerző:	Adegoke, Nurudeen A.
Cím:	Monitoring multivariate coefficient of variation for high-dimensional processes / Nurudeen A. Adegoke, Abdaljbbar Dawod, Olatunde Adebayo Adeoti, Ridwan A. Sanusi, Saddam Akber Abbasi
Dátum:	2022
ISSN:	0748-8017
Megjegyzések:	Multivariate coefficient of variation (MCV) charts are effective tools for monitoring process relative variability. They are developed on the assumption that the process subgroup size available for monitoring the MCV parameter is larger than the number of process characteristics.Insuchacase,the unbiasedestimates of the in-control mean vector and covariance matrix are used to calculate the chartmonitoringstatistic.Here,westudytheperformanceofMCVcontrolcharts when only a small subgroup size is available for estimating the in-control mean vector and covariance matrix. We examine the use of a shrinkage estimate of the covariance matrix and propose two one-sided upward and downwardleast absolute shrinkage and selection operator (LASSO)-based MCV charts for detecting upward and downward shifts in the process MCV parameter, respectively. Our simulation study shows that the LASSO-based MCV charts outperform the classical twoone-sided MCVchartswhensmallsub group sizes a reavailable for monitoring. The improvedperformanceofthe proposed LASSO-based MCV chartsin monitoring shifts in the MCV parameter is demonstrated via an illustrative case study of carbon fiber tube application, where changes are detected earlier than the classical two one-sided MCV charts.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk high-dimensional LASSO likelihood ratio test process monitoring relative variability shrinkage covariance matrix
Megjelenés:	Quality And Reliability Engineering International. - 38 : 5 (2022), p. 2606-2621. -
További szerzők:	Dawod, Abdaljbbar Babiker Abdaljbbar (1987-) (Ph.D. student) Adeoti, Olatunde Adebayo Sanusi, Ridwan A. Abbasi, Saddam Akber
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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