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dc.contributor.advisorArtiles-León, Noel
dc.contributor.authorMézquita-Fabián, Orlando J.
dc.date.accessioned2018-11-28T13:22:35Z
dc.date.available2018-11-28T13:22:35Z
dc.date.issued2011
dc.identifier.urihttps://hdl.handle.net/20.500.11801/1502
dc.description.abstractIn this thesis two control charts for monitoring the dispersion of a variable are designed and compared. Both charts are based on an Exponentially Weighted Moving Average (EWMA) and the inverse normal transformation is used to improve the ability of the charts for detecting a change in the variability of the variable that is being monitored.A control chart with two control limits was introduced to monitor increases and decreases in the dispersion of the process and a control chart with one control limit was introduced to monitor increases in process dispersion. The Average Run Length (ARL) of the charts was obtained using Markov Chains and the design of the charts was made possible through regression functions that provide optimal values for parameters λ and K. When comparing the charts, we determined that the control chart with two control limits detects changes in process dispersion faster than the EWMA chart based on a logarithmic transformation, and faster than the control charts R and S for less than 50 percent increase in process dispersion. For the case of the control chart with one control limit, the performance was similar to the control chart based on a logarithmic transformation introduced by Crowder and Hamilton (1992) but have a better performance than charts R and S.en_US
dc.description.abstractEn esta tesis se diseñan y comparan dos gráficos de control, basados en el “Exponentially Weighted Moving Average” (EWMA), para monitorear la dispersión de una variable. En ambos casos, se le aplica la transformación de la normal inversa al estadístico EWMA para mejorar la habilidad de los gráficos para detectar cambios en la variabilidad de la variable que se monitorea. Se construyó un gráfico de control con dos límites para monitorear incrementos y disminuciones en la dispersión del proceso y otro con un límite de control para monitorear incrementos en la dispersión del proceso. El largo de corrida promedio (ARL) de los gráficos se calculó con cadenas de Markov y el diseño se hizo posible usando funciones de regresión que producen los valores óptimos de los parámetros λ y K. Al hacer las comparaciones, se determinó que el gráfico con dos límites de control supera consistentemente al gráfico EWMA con una transformación logarítmica y a los gráficos R y S para incrementos menores a un 50 por ciento en la dispersión del proceso. En el caso del gráfico con un límite de control, el desempeño fue similar al gráfico con una transformación logarítmica introducido por Crowder y Hamilton (1992) pero supera los gráficos R y S.en_US
dc.language.isoSpanishen_US
dc.subjectDispersion of a variableen
dc.subjectExponentially Weighted Moving Averageen
dc.subjectInverse normal transformationen
dc.titleDiseño de gráfico EWMA para la dispersión del proceso usando la transformación de la normal inversaen_US
dc.typeThesisen_US
dc.rights.licenseAll rights reserveden_US
dc.rights.holder(c)2011 Orlando José Mézquita Fabiánen_US
dc.contributor.committeeCarlo, Héctor J.
dc.contributor.committeeFerrer-Alameda, Mercedes
dc.contributor.representativeAmador Dumais, Maria
thesis.degree.levelM.S.en_US
thesis.degree.disciplineIndustrial Engineeringen_US
dc.contributor.collegeCollege of Engineeringen_US
dc.contributor.departmentDepartment of Industrial Engineeringen_US
dc.description.graduationSemesterSpring (2nd semester)en_US
dc.description.graduationYear2011en_US


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    Items included under this collection are theses, dissertations, and project reports submitted as a requirement for completing a degree at UPR-Mayagüez.

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