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

Vista sencilla de ítem
dc.contributor.authorDintén, R.es_ES
dc.contributor.authorLópez Martínez, P.es_ES
dc.contributor.authorZorrilla, M.es_ES
dc.contributor.funderGobierno de Españaes_ES
dc.contributor.funderEuropean Regional Development Fundes_ES
dc.date.accessioned2021-07-07T10:30:55Z
dc.date.available2021-07-07T10:30:55Z
dc.date.issued2021-07-01
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.en_EN
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.accrualMethodOJSes_ES
dc.description.bibliographicCitationDintén, 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.2021.14532es_ES
dc.description.issue3es_ES
dc.description.referencesAhmad, 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/10.1155/2018/6951318es_ES
dc.description.referencesAlcácer, 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.2019.01.006es_ES
dc.description.referencesAngulo, 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.2016.1145810es_ES
dc.description.referencesArantes, 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.2018.8369574es_ES
dc.description.referencesArantes, 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.2018.8369574es_ES
dc.description.referencesThe apache avro project: a data serialization system, http://avro. apache.org (accessed 30 April 2019).es_ES
dc.description.referencesApache Cassandra., http://cassandra.apache.org/ (accessed 30 April 2019).es_ES
dc.description.referencesApache 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.referencesApache Spark: A fast and general engine for large-scale data processing, http://spark.apache.org/ (accessed 30 Dec 2019).es_ES
dc.description.referencesApache 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.referencesApache Zookeeper., https://zookeeper.apache.org/ (accessed 30 April 2019).es_ES
dc.description.referencesBelman-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.2020.12579es_ES
dc.description.referencesChen, 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.referencesDíaz, 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/s00521-018-3850-1es_ES
dc.description.referencesEmpowering app development for developers | Docker, https://www.docker.com/ (accessed 28 September 2020)es_ES
dc.description.referencesGhobakhloo, 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-02-2018-0057es_ES
dc.description.referencesGuerriero, 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/10.1145/2896825es_ES
dc.description.referencesHermann, 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.2016.488es_ES
dc.description.referencesI. I. Consortium, Industrial internet reference architecture v1.9, http://www.iiconsortium.org/IIRA.htm, accessed 30 April 2019 (2019).es_ES
dc.description.referencesJunqueira. F., Reed B., ZooKeeper: Distributed process Coordination, O,Reilly, 2014.es_ES
dc.description.referencesKubernetes., https://kubernetes.io/ (accessed 18 Decemeber 2020)es_ES
dc.description.referencesMarino 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.referencesPérez-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/s10270-019-00730-3es_ES
dc.description.referencesPetrasch, 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.2016.7748885es_ES
dc.description.referencesRAMI 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.referencesPrometheus exporters, https://github.com/prometheus/node_exporter (accessed 30 April 2019).es_ES
dc.description.referencesPrometheus overview, https://prometheus.io/docs/introduction/overview/ (accessed 30 April 2019).es_ES
dc.description.referencesRAI4 deployment tool and metamodel, https://github.com/istr-uc/RAI4DeploymentTool (accessed 20 July 2020).es_ES
dc.description.referencesRajbhoj, 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.2014.23es_ES
dc.description.referencesRaptis, 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.2019.2929296es_ES
dc.description.referencesReza 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/ijgi8020099es_ES
dc.description.referencesSahal, 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.2019.11.004es_ES
dc.description.referencesSalkin, 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_1es_ES
dc.description.referencesThoben, 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.p0004es_ES
dc.description.referencesUngurean, 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/s20195603es_ES
dc.description.referencesVelásquez, 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.e29es_ES
dc.description.referencesWiesner, 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.2015.1130243es_ES
dc.description.referencesWingerath, 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-2016-0002es_ES
dc.description.referencesWortmann, 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.2017.14es_ES
dc.description.referencesYebenes, 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.referencesZhong, 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.2017.05.015es_ES
dc.description.referencesZorrilla, 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.2019.06.040es_ES
dc.description.sponsorshipEste 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.description.upvformatpfin311es_ES
dc.description.upvformatpinicio300es_ES
dc.description.volume18es_ES
dc.identifier.doi10.4995/riai.2021.14532
dc.identifier.eissn1697-7920
dc.identifier.issn1697-7912
dc.identifier.urihttps://riunet.upv.es/handle/10251/168916
dc.languageEspañoles_ES
dc.publisherUniversitat Politècnica de Valènciaes_ES
dc.relation.ispartofRevista Iberoamericana de Automática e Informática industriales_ES
dc.relation.pasarelaOJS\14532es_ES
dc.relation.projectIDinfo: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.relation.publisherversionhttps://doi.org/10.4995/riai.2021.14532es_ES
dc.relation.references10.1155/2018/6951318es_ES
dc.relation.references10.1016/j.jestch.2019.01.006es_ES
dc.relation.references10.1080/0951192X.2016.1145810es_ES
dc.relation.references10.1109/SYSCON.2018.8369574es_ES
dc.relation.references10.4995/riai.2020.12579es_ES
dc.relation.references10.1007/s00521-018-3850-1es_ES
dc.relation.references10.1108/JMTM-02-2018-0057es_ES
dc.relation.references10.1145/2896825es_ES
dc.relation.references10.1109/HICSS.2016.488es_ES
dc.relation.references10.1007/s10270-019-00730-3es_ES
dc.relation.references10.1109/JCSSE.2016.7748885es_ES
dc.relation.references10.1109/APSEC.2014.23es_ES
dc.relation.references10.1109/ACCESS.2019.2929296es_ES
dc.relation.references10.3390/ijgi8020099es_ES
dc.relation.references10.1016/j.jmsy.2019.11.004es_ES
dc.relation.references10.1007/978-3-319-57870-5_1es_ES
dc.relation.references10.20965/ijat.2017.p0004es_ES
dc.relation.references10.3390/s20195603es_ES
dc.relation.references10.24215/16666038.18.e29es_ES
dc.relation.references10.1080/0951192X.2015.1130243es_ES
dc.relation.references10.1515/itit-2016-0002es_ES
dc.relation.references10.1109/MODELS.2017.14es_ES
dc.relation.references10.1016/J.ENG.2017.05.015es_ES
dc.relation.references10.1016/j.cie.2019.06.040es_ES
dc.rightsReconocimiento - No comercial - Compartir igual (by-nc-sa)es_ES
dc.rights.accessRightsAbiertoes_ES
dc.subjectData-centric architecturees_ES
dc.subjectMetamodeles_ES
dc.subjectModel-based developmentes_ES
dc.subjectIndustrial applicationses_ES
dc.subjectIndustry 4.0es_ES
dc.subjectArquitectura centrada en el datoes_ES
dc.subjectMetamodeloes_ES
dc.subjectDesarrollo basado en modeloses_ES
dc.subjectAplicaciones industrialeses_ES
dc.subjectIndustria 4.0es_ES
dc.titleArquitectura de referencia para el diseño y desarrollo de aplicaciones para la Industria 4.0es_ES
dc.title.alternativeReference architecture for the design and development of applications for Industry 4.0es_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
upv.uuid627cf09d-05c2-4f9e-bb60-e03ae3a4290des_ES

Archivos

Bloque original

Mostrando 1 - 1 de 1
Miniatura
Nombre:
Dntén;López;Zorrlla - Arqutectura de referenca para el dseño y desarrollo de aplcacones para la I....pdf
Tamaño:
1.68 MB
Formato:
Adobe Portable Document Format
Descripción:
Versión editorial
[object Object] Descargar

Colecciones

Revista Iberoamericana de Automática e Informática Industrial - Vol 18, No 3 (2021)