Uso de tecnologías IoT para facilitar la comunicación humano – máquina: un caso de uso sobre la adquisición del tiempo de preparación

Número

Sección

Artículos
  • Paula Morella Tecnalia, Basque Research Technology Alliance (BRTA), 50018 Zaragoza, Spain.
  • María Pilar Lambán Department of Design and Manufacturing Engineering, University of Zaragoza, 50018 Zaragoza, Spain.
  • Jesús Royo Department of Design and Manufacturing Engineering, University of Zaragoza, 50018 Zaragoza, Spain.
  • Juan Carlos Sánchez TECNALIA, Basque Research Technology Alliance (BRTA), 50018 Zaragoza, Spain.

DOI:

https://doi.org/10.37610/88.694

Publicado

30-04-2026

Resumen

La Industria 4.0 ha revolucionado el paradigma de la industria. La combinación de sistemas ciberfísicos con tecnologías 4.0 ha supuesto la mejora del entorno industrial. Este artículo se centra en la combinación de sistemas ciberfísicos e IoT para facilitar la comunicación entre CPS y humanos, un tema en el que todavía no existen muchas investigaciones. In particular, esta investigación pretende superar el reto de conocer con precisión el tiempo de preparación de una máquina herramienta. El sistema de adquisición de la máquina no es capaz de medir el tiempo de preparación de la misma porque está apagada durante este proceso. Sin embargo, la incorporación de un dispositivo IoT adicional permite solucionar este problema. Este artículo presentar un caso de estudio que emplea un dispositivo IoT con RFID, de manera que el usuario pueda comunicarse con el CPS y saber cuál ha sido el tiempo de preparación de la máquina para calcular el OEE teniendo este tiempo en consideración o no. El estudio concluye que la tecnología IoT facilita la comunicación entre CPS y usuario y muestra la importancia de medir adecuadamente el tiempo de preparación para hacer una correcta evaluación del OEE, medir la productividad y poder definir estrategias de mejora.

Palabras clave:

Sistema ciberfísico, internet de las cosas, tiempo de preparación, tiempo real

Agencias de apoyo

  • This work is funded by FABRICARE project “Co-financed by CDTI and European Next Generation EU funds from the Recovery and Resilience Mechanism”.

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