Improved process capability assessment through semiparametric piecewise modeling

Simple item page
dc.contributor.authorSoares, Vinicius da Costa
dc.contributor.authorJerez-Lillo, Nixon
dc.contributor.authorFerreira, Paulo Henrique
dc.contributor.authorRamos, Pedro Luiz
dc.date.accessioned2025-01-20T16:14:45Z
dc.date.available2025-01-20T16:14:45Z
dc.date.issued2024
dc.description.abstractPiecewise models have gained popularity as a useful tool in reliability and quality control/monitoring, particularly when the process data deviates from a normal distribution. In this study, we develop maximum likelihood estimators (MLEs) for the process capability indices, denoted as $ C_{pk} $ Cpk, $ C_{pm} $ Cpm, $ C<^>{*}_{pm} $ Cpm & lowast; and $ C_{pmk} $ Cpmk, using a semiparametric model. To remove the bias in the MLEs with small sample sizes, we propose a bias-correction approach to obtain improved estimates. Furthermore, we extend the proposed method to situations where the change-points in the density function are unknown. To estimate the model parameters efficiently, we employ the profiled maximum likelihood approach. Our simulation study reveals that the suggested method yields accurate estimates with low bias and mean squared error. Finally, we provide real-world data applications to demonstrate the superiority of the proposed procedure over existing ones.
dc.fuente.origenWOS
dc.identifier.doi10.1080/00949655.2024.2366364
dc.identifier.eissn1563-5163
dc.identifier.issn0094-9655
dc.identifier.urihttps://doi.org/10.1080/00949655.2024.2366364
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/90458
dc.identifier.wosidWOS:001254101500001
dc.issue.numero14
dc.language.isoen
dc.pagina.final3092
dc.pagina.inicio3063
dc.revistaJournal of statistical computation and simulation
dc.rightsacceso restringido
dc.subjectBias-correction method
dc.subjectchange-point model
dc.subjectpiecewise exponential model
dc.subjectprocess capability index
dc.titleImproved process capability assessment through semiparametric piecewise modeling
dc.typeartículo
dc.volumen94
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
Files
Collections
Artículos de revistas