A Study of Cumulative Quantity Control Chart for a Mixture of Rayleigh Model under a Bayesian Framework

This study deals with the cumulative charting technique based on a simple and a mixture of Rayleigh models. The respective charting schemes are referred as the SRCQC-chart and the MRCQC-chart. These are stimulated from existing statistical control charts in this direction i.e. the cumulative quantity control (CQC) chart, based on exponential and Weibull models, and the cumulative count control (CCC) chart, based on the simple geometricmodel. Another motivation for this study is the mixture cumulative count control (MCCC) chart based on the two component geometric model. The use of mixture cumulative quantity is an attractive approach for process monitoring. The design structure of the proposed control chart is derived by using the cumulative distribution function of simple, and two components of mixture distribution(s). We observed that the proposed charting structure is efficient in detecting the changes in process parameters. The application of the proposed scheme is illustrated using a real dataset.

• Autores: Aslam, Muhammad; Riaz, Muhammad; Sindhu, Tabassum Naz; Ahmed, Zaheer
• Tipo de recurso: Article of journal
• Fecha de publicación: 2016
• Institución: Universidad Nacional de Colombia
• Repositorio: Universidad Nacional de Colombia
• Idioma: spa
• OAI Identifier: oai:repositorio.unal.edu.co:unal/66518
• Acceso en línea: https://repositorio.unal.edu.co/handle/unal/66518; http://bdigital.unal.edu.co/67546/
• Palabra clave: 51 Matemáticas / Mathematics; 31 Colecciones de estadística general / Statistics; Quality control; Inverse Transformation Method; Loss Functions and Bayes Estimators; MRCQC-Chart; SRCQC-Char; Control de calidad; Método de la transformación; Función de pérdida; Estimador bayesiano; Carta MRCQC; Carta SRCQC
• Rights: openAccess
• License: Atribución-NoComercial 4.0 Internacional