Simultaneously guaranteeing the in-control and out-of-control performances of the S-2 control chart with estimated variance

[EN] Recent studies on the effects of parameter estimation on control charts have focused on their conditional in-control (IC) performance and recommended either the minimum number of Phase I samples (m) or adjustments to the control limit factor (L) that guarantee a desired IC performance with a hi...

Descripción completa

Detalles Bibliográficos
Autores: Aparisi García, Francisco José|||0000-0001-9934-1355, Mosquera-Restrepo, Jaime, Kahn Epprecht, Eugenio
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/213922
Acceso en línea:https://riunet.upv.es/handle/10251/213922
Access Level:acceso abierto
Palabra clave:Adjusted control limit
ARL
Conditional performance
Estimation effect
S-2 control chart
ESTADISTICA E INVESTIGACION OPERATIVA
Descripción
Sumario:[EN] Recent studies on the effects of parameter estimation on control charts have focused on their conditional in-control (IC) performance and recommended either the minimum number of Phase I samples (m) or adjustments to the control limit factor (L) that guarantee a desired IC performance with a high probability. In most cases, the numbers of samples required are prohibitively large in practice, and the adjustments for smaller numbers of samples entail as a counterpart a deterioration of the chart's out-of-control (OOC) performance. This presents the user with a hard decision, in which he or she will have difficulty in finding the best compromise between the objectives of good (or acceptable) IC performance, OOC performance, and a practicable number of Phase I samples. Therefore, in the context of the S-2 chart, we propose a new approach that takes both the desired IC and OOC performances (that should be within specified tolerances with a specified high joint probability) as constraints for the optimization of the pair (L, m). This is the first work that simultaneously treats the choice of m and the control limit adjustment in the framework of an optimization problem. With our model, the user can automatically obtain the most feasible (minimum m) solution that satisfies his/her requirements on both the IC and OOC performances.