DISEÑO DE PLATAFORMAS TECNOLÓGICAS PARA ANALÍTICA DE BIG DATA EN SISTEMAS CIBER-FÍSICOS INDUSTRIALES
Resumen
A través de los sistemas de analítica industrial es posible identificar ideas, patrones o modelos útiles necesarios para la innovación sostenible. la creación de plataformas tecnológicas para promover servicios de optimización enfrenta los desafíos de los sistemas ciberfísicos industriales que deben considerar un enfoque novedoso para el diseño de una arquitectura de referencia que integre la convergencia de tecnologías en la analítica de Big Data industrial y el aprendizaje máquina. Este trabajo de investigación presenta un enfoque metodológico para el diseño de una arquitectura de referencia para analítica de Big Data industrial que provee servicios de optimización para la detección temprana de fallas en la industria 4.0 a través de los métodos basados en datos. La arquitectura de referencia fue validada en un escenario de Big Data industrial que incorpora dos servicios basados en almacenamiento HDFS. El primer servicio, Data Analytics Studio (DAS), extrae información basada en consultas SQL que permite generar vistas y nuevas tablas. El segundo servicio permite el análisis con Spark mediante un cuaderno de trabajo Zeppelin basado en la web para el análisis de datos en forma interactiva. Finalmente, se ha definido un marco de trabajo que sirve para agilizar y facilitar el diseño de soluciones de Big Data industrial, con una metodología de diseño para una arquitectura que permita integrar fases y herramientas para brindar soluciones a escenarios de uso concretos.Citas
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