Control estadístico de la media con datos censurados a intervalo
1 recurso en línea (páginas 89-96).
- Autores:
-
Conto López, Romario Ademir
González Alvarez, Nelfi Gertrudis
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2018
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uptc.edu.co:001/2147
- Acceso en línea:
- http://repositorio.uptc.edu.co/handle/001/2147
- Palabra clave:
- Control de calidad
Control de calidad - Métodos estadísticos
Análisis multivariante
Mejoramiento de procesos
Cartas de control
Censura
Monitoreo de procesos
- Rights
- openAccess
- License
- Copyright (c) 2018 Universidad Pedagógica y Tecnológica de Colombia
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Control estadístico de la media con datos censurados a intervalo |
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Statistical control of the mean in presence of interval-censored data |
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Control estadístico de la media con datos censurados a intervalo |
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Control estadístico de la media con datos censurados a intervalo Control de calidad Control de calidad - Métodos estadísticos Análisis multivariante Mejoramiento de procesos Cartas de control Censura Monitoreo de procesos |
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Control estadístico de la media con datos censurados a intervalo |
| title_full |
Control estadístico de la media con datos censurados a intervalo |
| title_fullStr |
Control estadístico de la media con datos censurados a intervalo |
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Control estadístico de la media con datos censurados a intervalo |
| title_sort |
Control estadístico de la media con datos censurados a intervalo |
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Conto López, Romario Ademir González Alvarez, Nelfi Gertrudis |
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Conto López, Romario Ademir González Alvarez, Nelfi Gertrudis |
| dc.subject.armarc.none.fl_str_mv |
Control de calidad Control de calidad - Métodos estadísticos Análisis multivariante Mejoramiento de procesos |
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Control de calidad Control de calidad - Métodos estadísticos Análisis multivariante Mejoramiento de procesos Cartas de control Censura Monitoreo de procesos |
| dc.subject.proposal.spa.fl_str_mv |
Cartas de control Censura Monitoreo de procesos |
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1 recurso en línea (páginas 89-96). |
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2018 |
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2018-09-05T21:16:17Z |
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2018-09-05T21:16:17Z |
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2018-03-05 |
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Conto López, R. A. & González Alvarez, N. G. (2018). Control estadístico de la media con datos censurados a intervalo. Ciencia en Desarrollo, 9(1), 89-96. https://doi.org/10.19053/01217488.v9.n1.2018.4668. http://repositorio.uptc.edu.co/handle/001/2147 |
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Conto López, R. A. & González Alvarez, N. G. (2018). Control estadístico de la media con datos censurados a intervalo. Ciencia en Desarrollo, 9(1), 89-96. https://doi.org/10.19053/01217488.v9.n1.2018.4668. http://repositorio.uptc.edu.co/handle/001/2147 2462-7658 10.19053/01217488.v9.n1.2018.4668 |
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H. S. Steiner y J. R. Mackay, “Monitoring processes with highly censored data”, Journal of Quality Technology, vol. 32, no. 3, pp. 199- 208, 2000. J. Vargas y T. Montaño, “Carta de control CEV X para distribuciones Weibull con datos censurados”, Revista Colombiana de Estadística, vol. 28, no. 2, pp. 125-139, 2005. Y. Chan,B. Han y F. Pascual “Monitoring the Weibull shape parameter with Type II censored data”, Quality and Reliability Engineering International, vol. 31, no. 5, pp. 741-760, 2015. B. Sadeghpour y M. Taghizadeh, “Optimal cusum control chart for censored reliability data with Log-logistic distribution", Computational Methods in Science and Technology, vol. 21, no. 4, pp. 221-227, 2015. Y. He, L. Wang, Z. He y Y. W e i , ‘Product reliability oriented design scheme of control chart based on the convergent CEV for censored characteristics", Mathematical Problems in Engineering, vol 2015, Article ID 128491, 11 pages, 2015. S. M. Raza, M. Moeen,M. Azad y A. F. Siddiqi, ‘Shewhart control charts for Rayleigh dis- tribution in the presence of type I censored data”, Journal of ISOSS, vol. 2, no. 2, pp. 210-217, 2016. C. Hsu, M. G. Taylor, S. Murray y D. Commenges, “Multiple imputation for interval cen- sored data with auxiliary variables”, Statistics in Medicine, vol. 25, pp. 769-781, 2006. A. Zyoud, F. A. Elfaki y M. Hrairi, “Nonparametric estimate based in imputations tech- niques for interval and partly interval censored data”, Science International (Lahore), vol. 28, no. 2, pp. 879-884, 2016. |
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Ciencia en Desarrollo;Volumen 9, número 1 (Enero-Junio 2018) |
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Copyright (c) 2018 Universidad Pedagógica y Tecnológica de Colombia |
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Conto López, Romario AdemirGonzález Alvarez, Nelfi Gertrudis2018-09-05T21:16:17Z2018-09-05T21:16:17Z2018-03-05Conto López, R. A. & González Alvarez, N. G. (2018). Control estadístico de la media con datos censurados a intervalo. Ciencia en Desarrollo, 9(1), 89-96. https://doi.org/10.19053/01217488.v9.n1.2018.4668. http://repositorio.uptc.edu.co/handle/001/21472462-7658http://repositorio.uptc.edu.co/handle/001/214710.19053/01217488.v9.n1.2018.46681 recurso en línea (páginas 89-96).En ocasiones, durante el monitoreo de procesos no es posible realizar mediciones exactas sobre las unidades observadas, por lo que se deberá trabajar con observaciones censuradas y, debido a esto, no sería apropiada una aplicación directa de las cartas de control tipo Shewhart tradicionales. Teniendo en cuenta esta situación, se debe recurrir a cartas de control que consideren el tipo de censura presente y una distribución adecuada para los datos. Para el caso de monitoreo sobre datos con censura a intervalo, bajo un esquema de inspección donde las unidades buenas son las que quedan censuradas y por ende se presenta alta censura en estado estable del proceso, se proponen tres cartas de control para , donde en cada una se imputa la censura de manera diferente, asumiendo distribución normal para la variable cuya media se controla, y censura tipo I. En la primera carta, cada observación censurada se reemplaza por el valor esperado condicional (CEV), en la segunda, se remplaza por el valor del límite superior de censura, y en la tercera, se remplaza por un valor aleatorio de una uniforme dentro del intervalo de censura. Mediante simulación se estudia la potencia en la detección de desviaciones de la media para las cartas propuestas y se compara con la carta Shewhart tradicional que ignora la censura.Occasionally, during the statistical process monitoring it is not possible to make measurements with precision on the observed units; therefore, it should be necessary to work with censored observations. Consequently, a direct application of the traditional Shewhart control charts would not be appropriate. Under these circumstances, it should be implemented control charts that include both the censoring involved and a suitable distribution for the resulting data. Under an inspection scheme, where no defective units are censored and a high censoring is presented on the stable state of the process, three control charts for are proposed, in the case of monitoring interval-censored data. Each of them has a different way to impute the censored data. In the first one, each censored observation is replaced by its conditional expected value (CEV); in the second one, the censored data is replaced by the upper limit of the interval which the censored data belongs to, and in the third one, it is replaced by a random value of a uniform distribution within the censoring interval, considering a typical distribution and censoring type I. The power for detecting deviations from the mean for the proposed charts is compared by means of simulation with the Shewhart chart that ignores censoring.Bibliografía: página 96.application/pdfspaUniversidad Pedagógica y Tecnológica de ColombiaCopyright (c) 2018 Universidad Pedagógica y Tecnológica de Colombiahttps://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial 4.0 Internacional (CC BY-NC 4.0)http://purl.org/coar/access_right/c_abf2https://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/view/4668/pdfControl estadístico de la media con datos censurados a intervaloStatistical control of the mean in presence of interval-censored dataArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionTexthttps://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85H. S. Steiner y J. R. Mackay, “Monitoring processes with highly censored data”, Journal of Quality Technology, vol. 32, no. 3, pp. 199- 208, 2000.J. Vargas y T. Montaño, “Carta de control CEV X para distribuciones Weibull con datos censurados”, Revista Colombiana de Estadística, vol. 28, no. 2, pp. 125-139, 2005.Y. Chan,B. Han y F. Pascual “Monitoring the Weibull shape parameter with Type II censored data”, Quality and Reliability Engineering International, vol. 31, no. 5, pp. 741-760, 2015.B. Sadeghpour y M. Taghizadeh, “Optimal cusum control chart for censored reliability data with Log-logistic distribution", Computational Methods in Science and Technology, vol. 21, no. 4, pp. 221-227, 2015.Y. He, L. Wang, Z. He y Y. W e i , ‘Product reliability oriented design scheme of control chart based on the convergent CEV for censored characteristics", Mathematical Problems in Engineering, vol 2015, Article ID 128491, 11 pages, 2015.S. M. Raza, M. Moeen,M. Azad y A. F. Siddiqi, ‘Shewhart control charts for Rayleigh dis- tribution in the presence of type I censored data”, Journal of ISOSS, vol. 2, no. 2, pp. 210-217, 2016.C. Hsu, M. G. Taylor, S. Murray y D. Commenges, “Multiple imputation for interval cen- sored data with auxiliary variables”, Statistics in Medicine, vol. 25, pp. 769-781, 2006.A. Zyoud, F. A. Elfaki y M. Hrairi, “Nonparametric estimate based in imputations tech- niques for interval and partly interval censored data”, Science International (Lahore), vol. 28, no. 2, pp. 879-884, 2016.Ciencia en Desarrollo;Volumen 9, número 1 (Enero-Junio 2018)Control de calidadControl de calidad - Métodos estadísticosAnálisis multivarianteMejoramiento de procesosCartas de controlCensuraMonitoreo de procesosORIGINALPPS_869_Control_estadistico_moda.pdfPPS_869_Control_estadistico_moda.pdfArchivo principalapplication/pdf1092310https://repositorio.uptc.edu.co/bitstreams/275d04ff-7f12-44f8-acb7-a5756f71f9c4/download7f02dfc660f1bafbe3313640274b2387MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-814798https://repositorio.uptc.edu.co/bitstreams/5386b16b-5415-4598-82d6-369cb552523f/download88794144ff048353b359a3174871b0d5MD52TEXTPPS-869.pdf.txtPPS-869.pdf.txtExtracted 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