A comparison of control charts for the average of autocorrelated processes
Control charts are extensively used with the purpose of monitoring some parameters of theprocess. In general these charts are based on the normality and independence assumptionsof the sample observations. However, there are situations where the independence is notvalid such as in chemical processes...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2009 |
| País: | Brasil |
| Institución: | Universidade Federal Fluminense (UFF) |
| Repositorio: | Sistemas & Gestão |
| Idioma: | portugués |
| OAI Identifier: | oai:ojs.www.revistasg.uff.br:article/45 |
| Acceso en línea: | https://www.revistasg.uff.br/sg/article/view/SGV3N1A5 |
| Access Level: | acceso abierto |
| Palabra clave: | Control Charts Autocorrelated Processes Geostatistics Monte Carlo Time Series Gráficos de controle Processos autocorrelacionados Geoestatística Séries temporais |
| Sumario: | Control charts are extensively used with the purpose of monitoring some parameters of theprocess. In general these charts are based on the normality and independence assumptionsof the sample observations. However, there are situations where the independence is notvalid such as in chemical processes or sampling on-line. In this paper we compared thecontrol charts based on geostatistics and time series methodologies with the well-knowncharts Shewhart, CUSUM and EWMA, when used to monitor the average of autocorrelatedprocesses. The comparison was performed by using Monte Carlo simulation implemented inthe software R for Windows. |
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