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Arquitectura de referencia para el diseño y desarrollo de aplicaciones para la Industria 4.0

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Arquitectura de referencia para el diseño y desarrollo de aplicaciones para la Industria 4.0

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dc.contributor.author Dintén, R. es_ES
dc.contributor.author López Martínez, P. es_ES
dc.contributor.author Zorrilla, M. es_ES
dc.date.accessioned 2021-07-07T10:30:55Z
dc.date.available 2021-07-07T10:30:55Z
dc.date.issued 2021-07-01
dc.identifier.issn 1697-7912
dc.identifier.uri http://hdl.handle.net/10251/168916
dc.description.abstract [EN] The real implementation of Industry 4.0 requires the reformulation and coordination of industrial processes. This requires defining a digital platform that integrates and facilitates communication and interaction between all elements involved in the value chain. There is currently no reference architecture (model) that helps organizations conceive, design and build this digital platform. This work provides a framework and includes a metamodel that describes the main elements involved in the digital platform (data, resources, applications and monitoring), as well as the information needed to configure, deploy and run applications on it. In addition, a tool conformed with this metamodel is provided. This automates the generation of configuration and launch files and their corresponding sending and execution on the platform nodes. Finally, the flexibility, extensibility and validity of the architecture and software artifacts built are shown through its application on a case study. es_ES
dc.description.abstract [ES] La implementación práctica de la Industria 4.0 requiere la reformulación y coordinación de los procesos industriales. Para ello se requiere disponer de una plataforma digital que integre y facilite la comunicación e interacción entre los elementos implicados en la cadena de valor. Actualmente no existe una arquitectura de referencia (modelo) que ayude a las organizaciones a concebir, diseñar e implantar esta plataforma digital. Este trabajo proporciona ese marco e incluye un metamodelo que recoge la descripción de todos los elementos involucrados en la plataforma digital (datos, recursos, aplicaciones y monitorización), así como la información necesaria para configurar, desplegar y ejecutar aplicaciones en ella. Asimismo, se proporciona una herramienta compatible con el metamodelo que automatiza la generación de archivos de configuración y lanzamiento y su correspondiente transferencia y ejecución en los nodos de la plataforma. Por último, se muestra la flexibilidad, extensibilidad y validez de la arquitectura y artefactos software construidos a través de su aplicación en un caso de estudio. es_ES
dc.description.sponsorship Este trabajo ha sido financiado en parte por el Gobierno de España y los fondos FEDER (AEI/FEDER, UE) en el proyecto TIN2017-86520-C3-3-R (PRECON-I4). es_ES
dc.language Español es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Revista Iberoamericana de Automática e Informática industrial es_ES
dc.rights Reconocimiento - No comercial - Compartir igual (by-nc-sa) es_ES
dc.subject Data-centric architecture es_ES
dc.subject Metamodel es_ES
dc.subject Model-based development es_ES
dc.subject Industrial applications es_ES
dc.subject Industry 4.0 es_ES
dc.subject Arquitectura centrada en el dato es_ES
dc.subject Metamodelo es_ES
dc.subject Desarrollo basado en modelos es_ES
dc.subject Aplicaciones industriales es_ES
dc.subject Industria 4.0 es_ES
dc.title Arquitectura de referencia para el diseño y desarrollo de aplicaciones para la Industria 4.0 es_ES
dc.title.alternative Reference architecture for the design and development of applications for Industry 4.0 es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/riai.2021.14532
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-86520-C3-3-R/ES/SISTEMAS INFORMATICOS PREDECIBLES Y CONFIABLES PARA LA INDUSTRIA 4.0/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Dintén, R.; López Martínez, P.; Zorrilla, M. (2021). Arquitectura de referencia para el diseño y desarrollo de aplicaciones para la Industria 4.0. Revista Iberoamericana de Automática e Informática industrial. 18(3):300-311. https://doi.org/10.4995/riai.2021.14532 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/riai.2021.14532 es_ES
dc.description.upvformatpinicio 300 es_ES
dc.description.upvformatpfin 311 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 18 es_ES
dc.description.issue 3 es_ES
dc.identifier.eissn 1697-7920
dc.relation.pasarela OJS\14532 es_ES
dc.contributor.funder Gobierno de España es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.description.references Ahmad, S., Badwelan, A., Ghaleb, A. M., Qamhan, A., Sharaf, M. Analyzing critical failures in a production process: is industrial iot the solution?, Wireless Communications and Mobile Computing (2018). https://doi.org/10.1155/2018/6951318 es_ES
dc.description.references Alcácer, V., Cruz-Machado, V. Scanning the industry 4.0: A literature review on technologies for manufacturing systems, Engineering Science and Technology, an International Journal 22 (3) (2019) 899 - 919. https://doi.org/10.1016/j.jestch.2019.01.006 es_ES
dc.description.references Angulo, P., Guzmán, C. C., Jiménez, G., Romero, D. A service-oriented architecture and its ict-infrastructure to support eco-efficiency performance monitoring in manufacturing enterprises, International Journal of Computer Integrated Manufacturing 30 (1) (2017) 202-214. arXiv:https://www.tandfonline.com/doi/pdf/10.1080/0951192X.2016.1145810, https://doi.org/10.1080/0951192X.2016.1145810 es_ES
dc.description.references Arantes, M., Bonnard, R., Mattei, A. P., Saqui-Sannes, P. de. General architecture for data analysis in industry 4.0 using sysml and model based system engineering, in: 2018 Annual IEEE International Systems Conference, SysCon 2018, Vancouver, BC, Canada, April 23-26, 2018, 2018, pp.1-6. https://doi.org/10.1109/SYSCON.2018.8369574 es_ES
dc.description.references Arantes, M., Bonnard, R., Mattei, A. P., Saqui-Sannes, P. de. General architecture for data analysis in industry 4.0 using sysml and model based system engineering, in: 2018 Annual IEEE International Systems Conference (SysCon), 2018, pp. 1-6. https://doi.org/10.1109/SYSCON.2018.8369574 es_ES
dc.description.references The apache avro project: a data serialization system, http://avro. apache.org (accessed 30 April 2019). es_ES
dc.description.references Apache Cassandra., http://cassandra.apache.org/ (accessed 30 April 2019). es_ES
dc.description.references Apache Kafka project: A distributed streaming platform, http://kafka. apache.org/ (accessed 30 April 2019). The Apache Software Foundation, http://www.apache.org/ (accessed 30 April 2019). es_ES
dc.description.references Apache Spark: A fast and general engine for large-scale data processing, http://spark.apache.org/ (accessed 30 Dec 2019). es_ES
dc.description.references Apache Storm: A fast and general engine for large-scale data processing, https://storm.apache.org/ (accessed 30 Dec 2019) Apache Zookeeper., https://zookeeper.apache.org/ (accessed 30 April 2019). es_ES
dc.description.references Apache Zookeeper., https://zookeeper.apache.org/ (accessed 30 April 2019). es_ES
dc.description.references Belman-López, C., Jiménez-García, J., & Hernández-González, S. (2020). Análisis exhaustivo de los principios de diseño en el contexto de Industria 4.0, Revista Iberoamericana de Automática e Informática industrial, 17(4), 432-447. https://doi.org/10.4995/riai.2020.12579 es_ES
dc.description.references Chen, Y., Feng, Q., Shi, W. An industrial robot system based on edge computing: An early experience, in: USENIX Workshop on Hot Topics in Edge Computing (HotEdge 18), USENIX Association, Boston, MA, 2018. es_ES
dc.description.references Díaz, G., Macià, H., Valero, V., Boubeta-Puig, J., Cuartero, F, An Intelligent Transportation System to control air pollution and road traffic in cities integrating CEP and Colored Petri Nets. Neural Computing and Applications 32(2): 405-426 (2020). https://doi.org/10.1007/s00521-018-3850-1 es_ES
dc.description.references Empowering app development for developers | Docker, https://www.docker.com/ (accessed 28 September 2020) es_ES
dc.description.references Ghobakhloo, M. The future of manufacturing industry: a strategic roadmap toward industry 4.0, Journal of Manufacturing Technology Management 29 (2018) 910-936. https://doi.org/10.1108/JMTM-02-2018-0057 es_ES
dc.description.references Guerriero, M., Tajfar, S., Tamburri, D. A., Di Nitto, E. Towards a model- driven design tool for big data architectures, in: Proceedings of the 2Nd International Workshop on BIG Data Software Engineering, BIGDSE '16, ACM, New York, NY, USA, 2016, pp. 37-43. https://doi.org/10.1145/2896825 es_ES
dc.description.references Hermann, M., Pentek, T., Otto, B. Design principles for industrie 4.0 scenarios, in: 2016 49th Hawaii International Conference on System Sciences (HICSS), 2016, pp. 3928-3937. https://doi.org/10.1109/HICSS.2016.488 es_ES
dc.description.references I. I. Consortium, Industrial internet reference architecture v1.9, http://www.iiconsortium.org/IIRA.htm, accessed 30 April 2019 (2019). es_ES
dc.description.references Junqueira. F., Reed B., ZooKeeper: Distributed process Coordination, O,Reilly, 2014. es_ES
dc.description.references Kubernetes., https://kubernetes.io/ (accessed 18 Decemeber 2020) es_ES
dc.description.references Marino F., Seitanidis I., Dao P., Bocchino S., Castoldi P., Salvadori C. IoT enabling PI: towards hyperconnected and interoperable smart containers, 6th International Physical Internet Conference, 2019, pp. 349-362. es_ES
dc.description.references Pérez-Palacín, D., Merseguer, J., Requeno, J. I., Guerriero, M., Di Nitto, E., Tamburri, D. A. A uml profile for the design, quality assessment and de- ployment of data-intensive applications, Software and Systems Modeling 18 (6) (2019) 3577-3614. https://doi.org/10.1007/s10270-019-00730-3 es_ES
dc.description.references Petrasch, R., Hentschke, R. Process modeling for industry 4.0 applications: Towards an industry 4.0 process modeling language and method, in: 2016 13th International Joint Conference on Computer Science and Software Engineering (JCSSE), 2016, pp. 1-5. https://doi.org/10.1109/JCSSE.2016.7748885 es_ES
dc.description.references RAMI 4.0, Reference architectural model industrie 4.0, https://www. plattform-i40.de/PI40/Redaktion/EN/Downloads/Publikation/rami40-an-introduction.html, accessed 30 Dec 2019 (2018). es_ES
dc.description.references Prometheus exporters, https://github.com/prometheus/node_exporter (accessed 30 April 2019). es_ES
dc.description.references Prometheus overview, https://prometheus.io/docs/introduction/overview/ (accessed 30 April 2019). es_ES
dc.description.references RAI4 deployment tool and metamodel, https://github.com/istr-uc/RAI4DeploymentTool (accessed 20 July 2020). es_ES
dc.description.references Rajbhoj, A., Kulkarni, V., Bellarykar, N. Early experience with model-driven development of mapreduce based big data application, in: 2014 21st Asia- Pacific Software Engineering Conference, Vol. 1, 2014, pp. 94-97. https://doi.org/10.1109/APSEC.2014.23 es_ES
dc.description.references Raptis, T. P., Passarella, A., Conti, M. Data management in industry 4.0: State of the art and open challenges, IEEE Access 7 (2019) 97052-97093. https://doi.org/10.1109/ACCESS.2019.2929296 es_ES
dc.description.references Reza Delavar, M., Gholami, A., Reza Shiran, G., Rashidi, Y., Reza Nakhaeizadeh, G., Kurt Freda, Smaeil Hatefi Afshar, "A Novel Method for Improving Air Pollution Prediction Based on Machine Learning Approaches: A Case Study Applied to the Capital City of Tehran". ISPRS Int. J. Geo-Information 8(2): 99m 2019. https://doi.org/10.3390/ijgi8020099 es_ES
dc.description.references Sahal, R., Breslin, J. G., Ali, M. I. Big data and stream processing platforms for industry 4.0 requirements mapping for a predictive maintenance use case, Journal of Manufacturing Systems 54 (2020) 138 - 151. https://doi.org/10.1016/j.jmsy.2019.11.004 es_ES
dc.description.references Salkin, C., Oner, M., Ustundag, A., Cevikcan, E. A Conceptual Framework for Industry 4.0, Springer International Publishing, Cham, 2018, pp. 3-23. https://doi.org/10.1007/978-3-319-57870-5_1 es_ES
dc.description.references Thoben, K.-D., Wiesner, S., Wuest, T. "industrie 4.0" and smart manufacturing - a review of research issues and application examples, International Journal of Automation Technology 11 (1) (2017) 4-16. https://doi.org/10.20965/ijat.2017.p0004 es_ES
dc.description.references Ungurean, I., Gaitan, N.C. A Software Architecture for the Industrial Internet of Things-A Conceptual Model, Sensors 2020, 20, 5603. https://doi.org/10.3390/s20195603 es_ES
dc.description.references Velásquez, N., Estevez, E., Pesado, P. Cloud computing, big data and the industry 4.0 reference architectures, Journal of Computer Science and Technology 18 (03) (2018) e29. https://doi.org/10.24215/16666038.18.e29 es_ES
dc.description.references Wiesner, S., Thoben, K.-D. Requirements for models, methods and tools supporting servitisation of products in manufacturing service ecosystems, International Journal of Computer Integrated Manufacturing (2016) 1- 11. https://doi.org/10.1080/0951192X.2015.1130243 es_ES
dc.description.references Wingerath, W., Gessert, F., Friedrich, S., Ritter, N. "Real-time stream processing for big data", Information Technology 4 (58) (2016) 186-194. https://doi.org/10.1515/itit-2016-0002 es_ES
dc.description.references Wortmann, A., Combemale, B., Barais, O. A systematic mapping study on modeling for industry 4.0, in: 2017 ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems (MODELS), 2017, pp. 281-291. https://doi.org/10.1109/MODELS.2017.14 es_ES
dc.description.references Yebenes, J., Zorrilla, M. Towards a data governance framework for third generation platforms, Procedia Computer Science The 2nd International Conference on Emerging Data and Industry 4.0 (EDI40) (2019). es_ES
dc.description.references Zhong, R. Y., Xu, X., Klotz, E., Newman, S. T. Intelligent manufacturing in the context of industry 4.0: A review, Engineering 3 (5) (2017) 616 - 630. https://doi.org/10.1016/J.ENG.2017.05.015 es_ES
dc.description.references Zorrilla, M. E., Ibrain, Á. Bernard, an energy intelligent system for raising residential users awareness, Computers & Industrial Engineering 135 (2019) 492-499. https://doi.org/10.1016/j.cie.2019.06.040 es_ES


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