Análisis exhaustivo de los principios de diseño en el contexto de Industria 4.0

C. E. Belman-Lopez, J. A. Jiménez-García, S. Hernández-González

Resumen

Los sistemas de producción han evolucionado los últimos años gracias a avances tecnológicos recientes e innovaciones en el proceso de manufactura. El termino Industria 4.0 se ha convertido en prioridad y objeto de estudio para empresas, centros de investigación y universidades, sin existir un consenso generalmente aceptado del término. Como resultado es difícil diseñar e implementar soluciones de Industria 4.0 a nivel académico, científico o empresarial. La contribución de este documento se centra en proporcionar un análisis del significado e implicaciones de Industria 4.0 y exponer de forma detallada 17 principios de diseño fundamentales obtenidos a través de un estudio de mapeo sistemático. Estos principios son eficiencia, integración, flexibilidad, descentralización, personalización, virtualización, seguridad, es holística, orientada a servicios, ubicua, colaborativa, modular, robusta, utiliza información en tiempo real, toma decisiones optimizadas por datos, equilibra la vida laboral y es autónoma e inteligente. A través de estos principios, ingenieros e investigadores están capacitados para investigar e implementar escenarios apropiados de Industria 4.0.


Palabras clave

Industria 4.0; sistemas de fabricación flexible e inteligente; cuarta revolución industrial; modelado y control de sistemas de fabricación; automatización

Clasificación por materias

Automatización de sistemas de producción;Sistemas de tiempo real e informática industrial

Texto completo:

PDF

Referencias

Ahmad, A., & Babar, M. (2016). Software architectures for robotic systems: A systematic mapping study. The Journal of Systems and Software, 16-39. https://doi.org/10.1016/j.jss.2016.08.039

Alexopoulos, K., Sipsas, K., Xanthakis, E., Makris, S., & Mourtzis, D. (2018). An industrial Internet of things based platform for context-aware information services in manufacturing. International Journal of Computer Integrated Manufacturing, 1-14. https://doi.org/10.1080/0951192X.2018.1500716

Almada-Lobo, F. (2015). The Industry 4.0 revolution and the future of Manufacturing Execution Systems (MES). Journal of Innovation Management, 16-21. https://doi.org/10.24840/2183-0606_003.004_0003

Angulo, P., Guzmán, C., Jiménez, G., & Romero, D. (2016). A service-oriented architecture and its ICT infrastructure to support eco-efficiency performance monitoring in manufacturing enterprises. International Journal of Computer Integrated Manufacturing, 202-214. https://doi.org/10.1080/0951192X.2016.1145810

Babiceanua, R., & Seker, R. (2016). Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook. Computers in Industry, 128-137. https://doi.org/10.1016/j.compind.2016.02.004

Bagheri, B., Yang, S., Kao, H.-A., & Lee, J. (2015). Cyber-physical Systems Architecture for Self-Aware Machines in Industry 4.0 Environment. IFAC- PapersOnLine, 1622 - 1627. https://doi.org/10.1016/j.ifacol.2015.06.318

Beysolow II, T. (2017). Introduction to Deep Learning Using R. San Francisco, California, USA: Apress. https://doi.org/10.1007/978-1-4842-2734-3

Bibby, L., & Dehe, B. (2018). Defining and assessing industry 4.0 maturity levels – case of the defence sector. Production Planning & Control, 1-15. https://doi.org/10.1080/09537287.2018.1503355

Brettel, M., Friederichsen, N., Keller, M., & Rosenberg, M. (2014). How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective. International Journal of Information and Communication Engineering, 1-8.

Caggiano, A. (2018). Cloud-based manufacturing process monitoring for smart diagnosis services. International Journal of Computer Integrated Manufacturing, 31(7), 612-623. https://doi.org/10.1080/0951192X.2018.1425552

Cervantes Maceda, H., Velasco-Elizondo, P., & Castro Careaga, L. (2016). Arquitectura de Software. Conceptos y ciclo de desarrollo. Ciudad de México, México: CENGAGE Learning.

Charro, A., & Schaefer, D. (2018). Cloud Manufacturing as a new type of Product- Service System. International Journal of Computer Integrated Manufacturing, 1018-1033. https://doi.org/10.1080/0951192X.2018.1493228

Chen, T., & Tsai, H.-R. (2016). Ubiquitous manufacturing: Current practices, challenges, and opportunities. Robotics and Computer-Integrated Manufacturing, 1-7. https://doi.org/10.1016/j.rcim.2016.01.001

Chen, X.-W., & Lin, X. (2014). Big Data Deep Learning: Challenges and Perspectives. IEEE Xplore, 514 - 525. https://doi.org/10.1109/ACCESS.2014.2325029

Chen, Y. (2017). Integrated and Intelligent Manufacturing: Perspectives and Enablers. Engineering, 588–595. https://doi.org/10.1016/J.ENG.2017.04.009

Chiu, Y.-C., Cheng, F.-T., & Huang, H.-C. (2017). Developing a factory-wide intelligent predictive maintenance system based on Industry 4.0. Journal of the Chinese Institute of Engineers, 1-11. https://doi.org/10.1080/02533839.2017.1362357

Ciffolilli, A., & Muscio, A. (2018). Industry 4.0: national and regional comparative advantages in key enabling technologies. European Planning Studies, 1-22. https://doi.org/10.1080/09654313.2018.1529145

Clusterplattform Deutschland . (2019). Clusterplattform Deutschland. Obtenido de Clusterplattform Deutschland: https://www.clusterplattform.de/CLUSTER/Navigation/DE/Home/home.html

Cobo, M., Jürgens, B., Herrero-Solana, V., Herrera-Viedma, E., & Martínez, M. (2018). Industry 4.0: a perspective based on bibliometric analysis. Procedia Computer Science, 364–371. https://doi.org/10.1016/j.procs.2018.10.278

Crawford, M., & ASME.org. (01 de Julio de 2018). How Industry 4.0 Impacts Engineering Design. Obtenido de ASME: https://www.asme.org/engineering- topics/articles/manufacturing-design/industry-40-impacts-engineering-design

definicionde.org. (27 de Diciembre de 2016). Definición de ubicuo - Que es según la RAE? Obtenido de Definición de las palabras: http://definicionde.org/ubicuo/

Delaram, J., & Valilai, O. (2016). Development of a Novel Solution to Enable Integration and Interoperability for Cloud Manufacturing. Procedia CIRP, 6-11. https://doi.org/10.1016/j.procir.2016.07.056

Delicato, F., Al-Anbuky, A., & Wang, K.-K. (2019). Editorial: Smart Cyber–Physical Systems: Toward Pervasive Intelligence systems. Future Generation Computer Systems, 1-6. https://doi.org/10.1016/j.future.2019.06.031

Deloitte. (05 de 10 de 2018). ¿Qué es la Industria 4.0? Obtenido de Deloite.: https://www2.deloitte.com/es/es/pages/manufacturing/articles/que-es-la- industria-4.0.html

Dilberoglua, U., Bahar, G., Yaman, U., & Dolen, M. (2017). The role of additive manufacturing in the era of Industry 4.0. International Conference on Flexible Automation and Intelligent Manufacturing (págs. 1-10). Italia: Procedia Manufacturing. https://doi.org/10.1016/j.promfg.2017.07.148

European Secretariat for Cluster Analysis. (2017). Quality audit: Gold Label of the European Cluster Excellence Initiative (ECEI). Obtenido de ESCA: https://www.cluster-analysis.org/gold-label-new

Evans, P., & Annunziata, M. (26 de Noviembre de 2012). Industrial Internet: Pushing the Boundaries of Minds and Machines. Obtenido de GE: https://www.ge.com/docs/chapters/Industrial_Internet.pdf

Fatorachian, H., & Kazemi, H. (2018). A critical investigation of Industry 4.0 in manufacturing: theoretical operationalisation framework. Production Planning & Control, 633-644. https://doi.org/10.1080/09537287.2018.1424960

Federal Minister of Education and Research. (2013). Deutschlands Spitzencluster Germany’s Leading-Edge Clusters. Obtenido de Federal Ministry of Education and Research (BMBF): https://www.hamburg.de/contentblob/2593364/3113df3e6f569c97b937bd8747 5564db/data/deutschlands-spitzencluster.pdf

Ferreira,, J., Sarraipa, J., Ferro-Beca, M., Agostinho, C., Costa, R., & Jardim-Goncalves, R. (2016). End-to-end manufacturing in factories of the future. International Journal of Computer Integrated Manufacturing, 1-14. https://doi.org/10.1080/0951192X.2016.1185155

Fettermann, D., Cavalcante, C., Domingues de Almeida, T., & Tortorella, G. (2018). How does Industry 4.0 contribute to operations management? Journal of Industrial and Production Engineering, 1-15. https://doi.org/10.1080/21681015.2018.1462863

Francalanza, E., Borg, J., & Constantinescu, C. (2018). Approaches for handling wicked manufacturing system design problems. Procedia CIRP, 67, 134-139. https://doi.org/10.1016/j.procir.2017.12.189

García, M., Irisarri, E., Pérez, F., Estévez, E., & Marcos, M. (2017). Arquitectura de Automatización basada en Sistemas Ciberfísicos para la Fabricación Flexible en la Industria de Petróleo y Gas. Revista Iberoamericana de Automática e Informática Industrial, 1-11. https://doi.org/10.4995/riai.2017.8823

Germany Trade & Invest (GTAI). (1 de Julio de 2014). Industrie 4.0 Smart Manufacturing for the future. Obtenido de Germany Trade & Invest (GTAI): https://www.gtai.de/GTAI/Content/CN/Invest/_SharedDocs/Downloads/GTAI/ Brochures/Industries/industrie4.0-smart-manufacturing-for-the-future-en.pdf

Ghobakhloo, M. (2019). Determinants of information and digital technology implementation for smart manufacturing. International Journal of Production Research, 1-23. https://doi.org/10.1080/00207543.2019.1630775

Götz, M., & Jankowska, B. (2017). Clusters and Industry 4.0 – do they fit together? European Planning Studies, 1633-1653. https://doi.org/10.1080/09654313.2017.1327037

Gregor, S. (2002). A Theory of Theories in Information Systems. Information Systems Foundations. Building the Theoretical, 1 - 20.

Gregor, S. (2009). Building Theory in the Sciences of the Artificial. Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (págs. 1- 10). Philadelphia, Pennsylvania, USA: ACM Digital Library. https://doi.org/10.1145/1555619.1555625

Henzel, R., & Herzwurm, G. (2018). Cloud Manufacturing: A state-of-the-art survey of current issues. CIRP, 947–952. https://doi.org/10.1016/j.procir.2018.03.055

Hermann, M., Otto, B., & Pentek, T. (2015). Design Principles for Industrie 4.0 Scenarios: A Literature Review. ResearchGate, 1-16. https://doi.org/10.13140/RG.2.2.29269.22248

Hernández A., A., Figueroa F., V., & Jiménez G., J. (2018). Propuesta de una metodología de diagnóstico para identificar los requerimientos tecnológicos de una empresa tradicional de manufactura para evolucionar a Industria 4.0. Celaya, Guanajuato, México: Tecnológico Nacional de México en Celaya.

Huang, S., & Yan, Y. (2019). Design of delayed reconfigurable manufacturing system based on part family grouping and machine selection. International Journal of Production Research, 1-19. https://doi.org/10.1080/00207543.2019.1654631

Ibarra, D., Ganzarain, J., & Igartua, J. (2017). Business model innovation through Industry 4.0: A review. Procedia Manufacturing, 4-10. https://doi.org/10.1016/j.promfg.2018.03.002

Jardim-Goncalves, R., Romero, D., & Grilo, A. (2017). Factories of the future: challenges and leading innovations in intelligent manufacturing. International Journal of Computer Integrated Manufacturing, 30, 4-14.

Jazdi, N. (17 de Jolio de 2014). Cyber Physical Systems in the Context of Industry 4.0. IEEE International Conference on Automation, Quality and Testing, Robotics. (págs. 1-3). Cluj-Napoca, Romania: IEEE. https://doi.org/10.1109/AQTR.2014.6857843

Kagermann, H., Wahlster, W., & Helbig, J. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0. Final report of the Industrie 4.0 Working Group. National Academy of Science and Engineering (acatech)., 1-82.

Kamble, S., Gunasekaran, A., & Gawankar, S. (2018). Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection, 408–425. https://doi.org/10.1016/j.psep.2018.05.009

Khan, K., Kunz, R., Kleijnen, J., & Antes, G. (2003). Five steps to conducting a systematic review. Journal of the royal society of medicine, 118-121. https://doi.org/10.1177/014107680309600304

Kipper, L., Furstenau, L., Hoppe, D., Frozza, R., & Iespen, S. (2019). Scopus scientific mapping production in industry 4.0 (2011–2018): a bibliometric analysis. International Journal of Production Research, 1-24. doi:https://doi.org/10.1080/00207543.2019.1671625

Klingenberg, C. (2017). Industry 4.0: what makes it a revolution? EurOMA (págs. 1-11). ResearchGate.

Kusiak, A. (2017). Smart manufacturing. International Journal of Production Research, 508-517. https://doi.org/10.1080/00207543.2017.1351644

Laudante, E. (2017). Industry 4.0, Innovation and Design. A new approach for ergonomic analysis in manufacturing system. An International Journal for All Aspects of Design, 1-12. https://doi.org/10.1080/14606925.2017.1352784

Lee, J., Ardakani, H., Yang, S., & Bagheri, B. (2015). Industrial big data analytics and cyber-physical systems for future maintenance & service innovation. Procedia CIRP, 3-7. https://doi.org/10.1016/j.procir.2015.08.026

Lee, J., Bagheri, B., & Kao, H.-A. (2014). A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems. Society of Manufacturing Engineers (SME), 18- 23. https://doi.org/10.1016/j.mfglet.2014.12.001

Lee, J., Kao, H.-A., & Yang, S. (2014). Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment. Procedia CIRP, 16, 3-8. https://doi.org/10.1016/j.procir.2014.02.001

Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 1–10. https://doi.org/10.1016/j.jii.2017.04.005

Luque, A., Peralta, E., De las Heras, A., & Córdoba, A. (2017). State of Industry 4.0 in the Andalusian food sector. Procedia Manufacturing, 1199-1205. https://doi.org/10.1016/j.promfg.2017.09.195

Macchi, D., & Solari, M. (2012). Mapeo sistemático de la literatura sobre la Adopción de Inspecciones de Software. Universidad ORT de Uruguay, 1 - 8.

MIT Technology Review. (31 de Octubre de 2018). "Digital twin", un gemelo virtual para aconsejar a la Industria 4.0. Obtenido de MIT Technology Review: https://www.technologyreview.es/s/10696/digital-twin-un-gemelo-virtual-para- aconsejar-la-industria-40

Moghaddam, S., Houshmand, M., Saitou, K., & Valilai, O. (2019). Configuration design of scalable reconfigurable manufacturing systems for part family. International Journal of Production Research, 1-24. https://doi.org/10.1080/00207543.2019.1620365

Moktadir, M., Ali, S., Kusi-Sarpong, S., & Ali Shaikh, M. (2018). Assessing challenges for implementing Industry 4.0: Implications for process safety and environmental protection. Process Safety and Environmental Protection, 730– 741. https://doi.org/10.1016/j.psep.2018.04.020

Muhuri, P., Shukla, A., & Abraham, A. (2019). Industry 4.0: A bibliometric analysis and detailed overview. Engineering Applications of Artificial Intelligence, 218– 235. https://doi.org/10.1016/j.engappai.2018.11.007

Nassehi, A., Schaefer, D., Wu, D., Xu, X., & Zaeh, M. (2018). Special issue on ‘Cyber-physical product creation for Industry 4.0’. International Journal of Computer Integrated Manufacturing, 611-611. https://doi.org/10.1080/0951192X.2018.1482106

Netzwerk Smart Production. (01 de Enero de 2019). Smart Production. Obtenido de Netzwerk Smart Production: https://www.smartproduction.de/

Neugebauer, R., Hippmann, S., Leis, M., & Landherr, M. (2016). Industrie 4.0 - From the Perspective of Applied Research. Procedia CIRP, 57, 2-7. https://doi.org/10.1016/j.procir.2016.11.002

NIST. (16 de Abril de 2018). Framework for Improving Critical Infrastructure Cybersecurity. Obtenido de National Institute of Standards and Technology: https://nvlpubs.nist.gov/nistpubs/CSWP/NIST.CSWP.04162018.pdf

Nodehi, T., Jardim-Goncalves, R., Zutshi, A., & Grilo, A. (2015). ICIF: an intercloud interoperability framework for computing resource cloud providers in factories of the future. International Journal of Computer Integrated Manufacturing, 1-12. https://doi.org/10.1080/0951192X.2015.1067921

Nunes, M., Pereira, A., & Alves, A. (2017). Smart products development approches for Industry 4.0. Manufacturing Engineering Society International Conference (págs. 1215-1222). Vigo, España: Procedia Manufacturing. https://doi.org/10.1016/j.promfg.2017.09.035

Oesterreich, T., & Teuteberg, F. (2016). Understanding the implications of digitisation and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry. Computers in Industry, 121-139. https://doi.org/10.1016/j.compind.2016.09.006

Packianathera, M., Davies, A., Harraden, S., Soman, S., & White, J. (2017). Data mining techniques applied to a manufacturing SME. Data mining techniques applied to a manufacturing SME, 123 – 128. https://doi.org/10.1016/j.procir.2016.06.120

Pereira, A., & Romero, F. (2017). A review of the meaning and the implications of the Industry 4.0 concept. En P. Manufacturing (Ed.), Manufacturing Engineering Society International Conference (págs. 1206-1214). Vigo, España: Elsevier. https://doi.org/10.1016/j.promfg.2017.09.032

Pereira, T., Barreto, L., & Amaral, A. (2017). Network and information security challenges within Industry 4.0 paradigm. Procedia Manufacturing, 1253-1260. https://doi.org/10.1016/j.promfg.2017.09.047

Piedrahita, A., & Vélez Ángel, P. (2017). Control de calidad en sistemas crowdsourcing: un mapeo sistemático. Scientia et Technica, 1 - 10. https://doi.org/10.22517/23447214.13541

Plattform Industrie 4.0. (2019). Plattform Industrie 4.0. Obtenido de Plattform Industrie 4.0: https://www.plattform- i40.de/PI40/Navigation/EN/ThePlatform/Background/background.html

Porter, M. (2000). Location, Competition, and Economic Development: Local Clusters in a Global Economy. Economic Development Quarterly, 15-34. https://doi.org/10.1177/089124240001400105

PWC. (01 de 01 de 2016). Industry 4.0: Building the Digital Enterprise. Obtenido de PWC: https://www.pwc.com/gx/en/industries/industries-4.0/landing- page/industry-4.0-building-your-digital-enterprise-april-2016.pdf

Qin, J., Liu, Y., & Grosvenor, R. (2016). A Categorical Framework of Manufacturing for Industry 4.0 and Beyond. Procedia CIRP, 173-178. https://doi.org/10.1016/j.procir.2016.08.005

Quintana, G., & Solari, M. (2012). Estudio de Mapeo Sistemático sobre Experimentos de Generación Automática de Casos de Prueba Estructurales. Universidad ORT de Uruguay, 1-10.

Radziwon, A., Bilberg, A., Bogers, M., & Madsen, E. (2014). The Smart Factory: Exploring Adaptive and Flexible Manufacturing Solutions. Procedia Engineering, 1184 – 1190. https://doi.org/10.1016/j.proeng.2014.03.108

Roblek, V., Meško, M., & Krapež, A. (2016). A Complex View of Industry 4.0. SAGE, 1-11. https://doi.org/10.1177/2158244016653987

Rojko, A. (2017). Industry 4.0 Concept: Background and Overview. International Journal of Innovation Management, 1-14. https://doi.org/10.3991/ijim.v11i5.7072

Román-Ibáñez, V., Jimeno-Morenilla, A., & Pujol-López, F. (2018). Distributed monitoring of heterogeneous robotic cells. A proposal for the footwear industry 4.0. International Journal of Computer Integrated Manufacturing, 1-16. https://doi.org/10.1080/0951192X.2018.1529432

Rosin, F., Forget, P., Lamouri, S., & Pellerin, R. (2019). Impacts of Industry 4.0 technologies on Lean principles. International Journal of Production Research, 1-19. https://doi.org/10.1080/00207543.2019.1672902

Rossit, D., Tohmé, F., & Frutos, M. (2018). Industry 4.0: Smart Scheduling. International Journal of Production Research. https://doi.org/10.1080/00207543.2018.1504248

Russo, J., & Solari, M. (2017). Estudio de Mapeo Sistemático sobre Arquitecturas de Software para Big Data. Conferencia Iberoamericana en Software Engineering (págs. 1 - 14). Buenos Aires, Argentina: ResearchGate.

Schmidt, R., Möhring, M., Härting, R.-C., Reichstein, C., Neumaier, P., & Jozinović, P. (2015). Industry 4.0 - Potentials for Creating Smart Products: Empirical Research Results. Business Information Systems, 16–27. https://doi.org/10.1007/978-3-319-19027-3_2

Schuh, G., Potente, T., Wesch-Potente, C., Weber, A., & Prote, J.-P. (2014). Collaboration Mechanisms to increase Productivity in the Context of Industrie 4.0. Procedia CIRP, 51 - 56. https://doi.org/10.1016/j.procir.2014.05.016

Schumacher, A., Erol, S., & Sihn, W. (2016). A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. Procedia CIRP, 161 – 166. https://doi.org/10.1016/j.procir.2016.07.040

Shafiq, S., Sanin, C., Toro, C., & Szczerbicki, E. (2015). Virtual Engineering Object (VEO): Toward Experience-Based Design and Manufacturing for Industry 4.0. Cybernetics and Systems: An International Journal, 1-17. https://doi.org/10.1080/01969722.2015.1007734

Shariatzadeh, N., Lundholm, T., Lindberg, L., & Sivard, G. (2016). Integration of digital factory with smart factory based on Internet of Things. Procedia CIRP, 512 – 517. https://doi.org/10.1016/j.procir.2016.05.050

Shin, W., Dahlgaard, J., Dahlgaard-Park, S., & Kim, M. (2018). A Quality Scorecard for the era of Industry 4.0. Total Quality Management & Business Excellence, 1-19. https://doi.org/10.1080/14783363.2018.1486536

Siemens. (05 de 10 de 2018). Siemens España | El Futuro de la Industria 4.0. Obtenido de Siemens: https://w5.siemens.com/spain/web/es/el-futuro-de-la- industria/pages/el_futuro_de_la_industria.aspx

Škulj, G., Vrabič, R., Butala, P., & Sluga, A. (2015). Decentralised network architecture for cloud manufacturing. International Journal of Computer Integrated Manufacturing, 1-15. https://doi.org/10.1080/0951192X.2015.1066861

Sony, M. (2018). Industry 4.0 and lean management: a proposed integration model and research propositions. Production & Manufacturing Research, 416-432. https://doi.org/10.1080/21693277.2018.1540949

Talhi, A., Huet, J., Fortineau, V., & Lamouri, S. (2015). Towards a Cloud Manufacturing systems modeling methodology. IFAC, 288–293. https://doi.org/10.1016/j.ifacol.2015.06.096

Tamas, L., & Murar, M. (2018). Smart CPS: vertical integration overview and user story with a cobot. International Journal of Computer Integrated Manufacturing, 1-19. https://doi.org/10.1080/0951192X.2018.1535196

Telukdarie, A., Buhulaiga, E., Bag, S., Gupta, S., & Luo, Z. (2018). Industry 4.0 implementation for multinationals. Process Safety and Environmental Protection, 316–329. https://doi.org/10.1016/j.psep.2018.06.030

Theorin, A., Bengtsson, K., Provost, J., Lieder, M., Johnsson, C., Lundholm, T., & Lennartson, B. (2016). An event-driven manufacturing information system architecture for Industry 4.0. International Journal of Production Research, 1- 16. https://doi.org/10.1080/00207543.2016.1201604

Thilmany, J., & ASME.org. (17 de Mayo de 2018). Artificial Intelligence Transforms Manufacturing. Obtenido de ASME: https://www.asme.org/engineering-topics/articles/manufacturing-design/artificial-intelligence-transforms-manufacturing

Tian, W., & Zhao, Y. (2015). Optimized Cloud Resource Management and Scheduling. Morgan Kaufmann. https://doi.org/10.1016/C2013-0-13415-0

Tjahjono, B., Esplugues, C., Ares, E., & Pelaez, G. (2017). What does Industry 4.0 mean to Supply Chain? Procedia Manufacturing, 1175–1182. https://doi.org/10.1016/j.promfg.2017.09.191

Tortorella, G., & Fettermann, D. (2017). Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies. International Journal of Production Research, 1-14. https://doi.org//10.1080/00207543.2017.1391420

Tuptuk, N., & Hailes, S. (2018). Security of smart manufacturing systems. Journal of Manufacturing Systems, 93-106. https://doi.org/10.1016/j.jmsy.2018.04.007

Vaidya, Ambad, P., & Bhosle, S. (2018). Industry 4.0 – A Glimpse. Procedia Manufacturing, 20, 233-238. https://doi.org/10.1016/j.promfg.2018.02.034

Wang, B., & Ha-Brookshire, J. (2018). Exploration of Digital Competency Requirements within the Fashion Supply Chain with an Anticipation of Industry 4.0. International Journal of Fashion Design, Technology and Education, 1-11. https://doi.org/10.1080/17543266.2018.1448459

Wang, X., Givehchi, M., & Wang, L. (2017). Manufacturing system on the cloud: a case study on cloud-based process planning. Procedia CIRP, 39 – 45. https://doi.org/10.1016/j.procir.2017.03.103

Wang, X., Ong, S., & Nee, A. (2017). A comprehensive survey of ubiquitous manufacturing research. International Journal of Production Research, 604-628. https://doi.org/10.1080/00207543.2017.1413259

Weyer, S., Schmitt, M., Ohmer, M., & Gorecky, D. (2015). Towards Industry 4.0 - Standardization as the crucial challenge for highly modular, multi-vendor production systems. IFAC-PapersOnLine, 48(3), 579-584. https://doi.org/10.1016/j.ifacol.2015.06.143

Wiesner, S., & Thoben, K.-D. (2016). Requirements for models, methods and tools supporting servitisation of products in manufacturing service ecosystems. International Journal of Computer Integrated Manufacturing, 1-12. https://doi.org/10.1080/0951192X.2015.1130243

WordReference.com. (2005). ubicuo - definición - WordReference.com. Obtenido de WordReference.com: https://www.wordreference.com/definicion/ubicuo

Wu, D., Jennings, C., Terpenny, J., Gao, R., & Kumara, S. (2017). A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests. Journal of Manufacturing Science and Engineering, 1-10. https://doi.org/10.1115/1.4036350

Wuest, T., Daniel, W., Irgens, C., & Thoben, K.-D. (2016). Machine learning in manufacturing: advantages, challenges, and applications. Production & Manufacturing Research, 23-45. https://doi.org/10.1080/21693277.2016.1192517

Xu, L. D., & Duan, L. (2018). Big data for cyber physical systems in industry 4.0: a survey. Enterprise Information Systems, 1-23. https://doi.org/10.1080/17517575.2018.1442934

Xu, L., Xu, E., & Li, L. (2018). Industry 4.0: state of the art and future trends. International Journal of Production Research, 56, 2941–2962. https://doi.org/10.1080/00207543.2018.1444806

Zhong, R., Xu, X., Klotz, E., & Newman, S. (2017). Intelligent Manufacturing in the Context of Industry 4.0: A Review. Engineering, 616–630. https://doi.org/10.1016/J.ENG.2017.05.015

Zhonga, R., Wang, L., & Xu, X. (2017). An IoT-enabled Real-time Machine Status Monitoring Approach for Cloud Manufacturing. Procedia CIRP, 709 – 714. https://doi.org/10.1016/j.procir.2017.03.349

Zhou, K., Liu, T., & Zhou, L. (2016). Industry 4.0: Towards Future Industrial Opportunities and Challenges. International Conference on Fuzzy Systems and Knowledge Discovery (págs. 2147–2152). Zhangjiajie, China: IEEE. https://doi.org/10.1109/FSKD.2015.7382284

Abstract Views

4602
Metrics Loading ...

Metrics powered by PLOS ALM


 

Citado por (artículos incluidos en Crossref)

This journal is a Crossref Cited-by Linking member. This list shows the references that citing the article automatically, if there are. For more information about the system please visit Crossref site

1. The Role of Mixed Criticality Technology in Industry 4.0
José Simó, Patricia Balbastre, Juan Francisco Blanes, José-Luis Poza-Luján, Ana Guasque
Electronics  vol: 10  num.: 3  primera página: 226  año: 2021  
doi: 10.3390/electronics10030226



Creative Commons License

Esta revista se publica bajo una Licencia Creative Commons Attribution-NonCommercial-CompartirIgual 4.0 International (CC BY-NC-SA 4.0)

Universitat Politècnica de València     https://doi.org/10.4995/riai

e-ISSN: 1697-7920     ISSN: 1697-7912