Fuzzy-Control-Chart Methodology for Assessing Specification Compliance in Cervical Cytology Sampling

Authors

Keywords:

Cervical Cancer, Cytology Sampling, Fuzzy Specification Compliance, p-Fuzzy Control Chart

Abstract

Fuzzy control charts allow expanding and improving analysis of processes in the medical sampling. In cervical cytology sampling it is necessary to consider the process uncertainty, including analysis of imprecise data. This article proposes a methodology for assessing specification compliance of medical sampling using p-fuzzy control charts, which allow considering data inaccuracy, unlike the traditional control charts. This methodology is carried out on four steps: (i) Definition of variable and fuzzy specification limit, (ii) Fuzzification of the process data, (iii) Design of rules for fuzzy specification compliance, and (iv) Determination of fuzzy specification compliance. The p-fuzzy control chart was applied for assessing results of cervical cytology sampling and it allowed to adequately identify specification compliance and warnings of non-compliance.  Future work is integration of this methodology with other inference systems that allow quality improvement in the medical sampling area.

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Author Biographies

Juan Miguel Cogollo-Flórez, Instituto Tecnológico Metropolitano

Juan Cogollo es Profesor Asociado en el Departamento de Calidad y Producción del Instituto Tecnológico Metropolitano-ITM, Medellín, Colombia. Obtuvo el grado de Magíster en Ingeniería Administrativa de la Universidad Nacional de Colombia en 2011. Sus actuales áreas de interés son control de la calidad avanzado, modelado difuso, medición del desempeño y gestión de la calidad en cadenas de suministro

Myladis Cogollo, Universidad de Córdoba

Myladis Cogollo es Profesora Asociada en el Departamento de Matemáticas y Estadística de la Universidad de Córdoba, Montería, Colombia. Obtuvo el grado de Doctora en Ingeniería – Sistemas e Informática en 2016 y el grado de Magíster en Ciencias-Estadística en 2008, ambos de la Universidad Nacional de Colombia. Sus actuales áreas de interés son modelado predictivo, análisis de series de tiempo no lineales y ciencia de datos.

Mónica Arteaga, Universidad EAFIT

Mónica Arteaga es Profesora en la Escuela de Ciencias de la Universidad EAFIT, Medellín, Colombia. Obtuvo el grado de Magíster en Matemáticas Aplicadas de la Universidad EAFIT (Colombia) en 2017. Sus actuales áreas de interés son control estadístico de la calidad, análisis multivariado, lógica difusa e inteligencia artificial.

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Published

2021-04-26
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