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...
| Autores: | , , |
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| 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 |
| 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. |
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