Abstract
Industrial IoT-based Performance measuring and optimization is a critical and important challenge for Industry 4.0. Harnessing data integration across different industrial systems could optimize production and enable interoperability and seamless integration in a domain where proprietary and manufacturer-dependent protocols and data models has always prevailed. In this paper, we present OPTYFY, an IIOT Data Management platform which fosters semantics for monitoring Industrial IoT devices. OPTYFY gathers different IoT data under a particular formal semantics and visualizes in a dashboard several features. We also present a proof-of-concept which deals with features such as time, flow and rate of production to monitor and optimize the factory production process.
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Acknowledgments
This work is supported by the ITEA3 CITISIM project and ITEA3 SCRATCH project, all of them funded by the Centro Tecnológico de Desarrollo Industrial (CDTI) and the ITEA3 EU funding program.
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Delgado-Clavero, Á., Gómez-Berbís, J.M., de Amescua-Seco, A., Sánchez-Segura, MI., Medina-Domínguez, F. (2019). OPTYFY: Industrial IoT-Based Performance and Production Optimization Based on Semantics. In: Valencia-García, R., Alcaraz-Mármol, G., Del Cioppo-Morstadt, J., Vera-Lucio, N., Bucaram-Leverone, M. (eds) Technologies and Innovation. CITI 2019. Communications in Computer and Information Science, vol 1124. Springer, Cham. https://doi.org/10.1007/978-3-030-34989-9_13
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