La multinacional alemana informó que su planta en Monterrey, Nuevo León, especializada en equipos de baja tensión para el sector energético, está desarrollado un programa piloto de monitoreo de la Efectividad Global de sus Equipos (OEE, por sus siglas en inglés) en la plataforma industrial MindSphere y Amazon.
“En Siemens estamos enfocados en digitalizar nuestras plantas para hacer más eficiente y competitiva nuestra producción en México. En nuestra planta de Monterrey estamos concluyendo las pruebas piloto para monitorear en tiempo real las pruebas de productos que se fabrican como interruptores eléctricos para el segmento de residencial”, informó Jair Mexía,dDirector de Large Drives y líder de Digitalización de Siemens México y Centroamérica.
En joint venture con Amazon Web Services, Siemens Monterrey definió el caso de uso OEE & Maintenance para la implementación de la herramienta MindSphere, un sistema operativo de Siemens que permite lograr la interacción entre los equipos de producción y aplicaciones de acuerdo con las necesidades específicas del negocio, explicó el directivo.
MindSphere facilita el monitoreo en tiempo real de los parámetros que componen el cálculo de OEE, implementado en los equipos que representan el mayor tiempo de demora en el proceso de producción, brindando a los ingenieros de soporte la información necesaria para la toma de decisiones efectiva e implementar acciones de mejora.
La aplicación de OEE está desarrollada en MindSphere Versión 3.0, y se encuentra alojada en la nube de Amazon. Una vez terminada su implementación, redundará en acciones más rápidas y enfocadas en los problemas diarios; agregará valor a la fábrica y a sus procesos al ser capaces de realizar mejoras enfocadas en temas muy específicos de acuerdo con la información que se observa.
Jair Mexía resaltó que la OEE “también abre la puerta para mejorar otras soluciones que se puedan tener en la fábrica y que impacten favorablemente la producción, ya que se trata de una solución escalable a otras áreas críticas”.
En este sentido, Luis Alberto Rodríguez García, líder del Departamento de Digitalización en la fábrica de Monterrey de Siemens explicó que la aplicación de OEE “Puede mejorar otras soluciones de la fábrica como por ejemplo: en las remachadoras, en las soldadoras, y en general en el mantenimiento predictivo de los equipos en todas las líneas de producción; lo que significa que se deje de reaccionar ante los problemas y en su lugar puedan ser prevenidos al observar que un equipo está bajando su rendimiento”.
«Y es que a diferencia del pasado, cuando al comenzar un modelo de producción se tenía que calibrar directamente en cada uno de los equipos los rangos aceptables para cumplir los estándares de calidad, con MindSphere es posible monitorear la disponibilidad del equipo a través de variables como actividad, desempeño y calidad”, destacó.
La digitalización representa ventajas sustanciales para esta planta de Siemens, puesto que esta misma información se solía obtener luego de mucho trabajo manual, considerando que en una línea de producción de este tipo se fabrican alrededor de 100 o 150 mil breakers diarios.
“Ahora estamos concentrando toda la información en esta aplicación para tener un análisis en tiempo real. Conforme van saliendo las pruebas, se va cargando la información a un servidor y por medio de MindSphere se analiza para proporcionar las herramientas necesarias a los ingenieros, quienes analizan y toman decisiones más rápidas”, agregó Luis Alberto Rodríguez García.
Es así que la fábrica de Siemens Monterrey puede consultar información histórica basada en pilares estratégicos para revisar gráficamente cada línea de producción según las necesidades; ya sea de manera semanal, mensual, o según se requiera. Asimismo, se puede obtener vistas de ingeniería, que expresan con mayor detalle distintas partes del proceso; por ejemplo, tiempo de disparo (trip time).
Lo anterior ayuda a los ingenieros a ver los datos de diferentes breakers que se están produciendo, e identificar desviaciones dentro de los rangos establecidos para cada tipo de variable. Cuando ven variaciones pueden tomar decisiones sobre lo que hay que revisar de dichos modelos en específico. La implementación se puede hacer en un corto plazo y puede dar un valor agregado al negocio, que las empleará en sus 17 líneas de producción.
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