Tecnologías de la cuarta revolución industrial utilizadas en la manufactura para mejorar los indicadores de productividad: Una revisión

DOI: https://doi.org/10.31908/19098367.3149
Palabras clave: Industria 4.0, IoT, Computación en la Nube, Manufactura, Gestión, Productividad, Indicadores

Resumen

Las tecnologías de la cuarta revolución industrial han impactado y beneficiado a todos los procesos industriales en diferentes sectores, esto permite la optimización de los recursos en las organizaciones y a su vez, una mejora en su productividad. La adopción e implementación de tecnologías 4.0 ha crecido rápidamente en algunos países; en otros, sigue siendo un desafío. Este artículo presenta una revisión de la literatura sobre el uso de tecnologías 4.0 en las industrias, orientada a identificar las tecnologías más utilizadas, los sectores impactados y los indicadores de productividad beneficiados. Este estudio se realizó utilizando la plataforma Core of Science y la metodología PRISMA con la información proporcionada por las bases de datos Scopus y Web of Science. Los hallazgos indican que las tecnologías más utilizadas son el Internet de las cosas, la computación en la nube y big data. Por otro lado, la manufactura es la actividad del sector industrial con mayor influencia en estas tecnologías, seguida de la industria automotriz. Finalmente, hay evidencia de una cobertura deficiente del uso de tecnologías 4.0 en los países latinoamericanos y, más significativamente, en los países europeos.

Descargas

La descarga de datos todavía no está disponible.

Biografía del autor

line Yasmin Becerra Sánchez, Universidad Católica de Pereira

Es Ingeniera Electrónica, Especialista en Telecomunicaciones. Magíster en Ingeniería (Área Telecomunicaciones). Doctora en Ingeniería, en el área Telecomunicaciones de la Universidad Pontificia Bolivariana. Actualmente es profesora asociada de tiempo completo de la Facultad de Ciencias Básicas e Ingeniería de la Universidad Católica de Pereira e investigadora Asociada según Minciencias-Colombia del grupo de investigación Entre Ciencia e Ingeniería de la misma universidad. Sus áreas de interés son: Telecomunicaciones, Ingeniería de tráfico, Enrutamiento, Redes Móviles, Internet, IPv6, Tecnologías 4.0.

Jorge Enrique Herrera Arroyave, Universidad Católica de Pereira

Nació en Pereira, Risaralda- Colombia, el 06 de julio de 1980. Obtuvo el título de Ingeniero Mecánico en la Universidad Tecnológica de Pereira, Risaralda - Colombia, en 2010, su Maestría en Ingeniería Aeronáutica de la Universidad Autónoma de Nuevo León, San Nicolás de los Garza, Monterrey, México, en 2015. Actualmente es estudiante de doctorado en Ciencias Física de la Universidad Tecnológica de Pereira, desde 2016 es profesor vinculado a la Facultad de Ciencias Básicas e Ingeniería de la Universidad Católica de Pereira, Risaralda - Colombia. Su investigación ha estado relacionada con el diseño de máquinas, la dinámica estructural, las energías renovables y la manufactura.

Lloyd Herberth Herberth Morris Molina

Es ingeniero y magíster de la Universidad Nacional Experimental del Táchira en Venezuela, magíster de la Universidad de Alcalá y doctor en Ciencias Gerenciales de la Universidad de las Fuerzas Armadas. Antes de venir a Colombia, fue profesor de ingeniería industrial en la Universidad Nacional Experimental del Táchira en Venezuela, donde impartía cursos de producción. Además, ocupó diferentes cargos administrativos como jefe de Tesorería y director de la Maestría en Dirección de Empresas, y presidente de la Caja de Ahorros UNET. Morris tiene 22 años de experiencia en educación superior en Colombia y Venezuela. Además, el Dr. Morris tiene varios años de experiencia en la industria de la ingeniería de fabricación, por ejemplo, en LAFARGE como director de fabricación. El objetivo del Dr. Morris es mejorar los procesos en las operaciones de ingeniería mediante la incorporación de técnicas o herramientas matemáticas en los procesos de toma de decisiones para aumentar la productividad de los procesos operativos en entornos organizacionales.

Alonso Toro Lazo, Universidad Católica de Pereira

Ingeniero de Sistemas y Telecomunicaciones por la Universidad Católica de Pereira (Colombia), Magíster en Gestión y Desarrollo de Proyectos de Software por la Universidad Autónoma de Manizales (Colombia), Ph.D en Big Data Management en la Universidad de Salerno (Italia). Actualmente es profesor auxiliar de tiempo completo de la Facultad de Ciencias Básicas e Ingeniería en la Universidad Católica de Pereira e investigador Asociado del grupo de investigación Entre Ciencia e Ingeniería de la misma universidad. Entre sus principales áreas de investigación se encuentran la ingeniería de software, el aseguramiento de la calidad del software (SQA), el testing automatizado, Big data y tecnologías de la industria 4.0 (principalmente Inteligencia Artificial y Analítica de datos, Internet de las cosas para la industria –IIoT y Sistemas Ciber-físicos -CPS). El Prof. Toro es autor de más de 25 artículos en revistas indexadas y miembro de comités académicos internacionales como el CICCSI (Argentina), PMI capítulo Italia e IEEE Latinoamérica.

Citas

S. T. N. Ray Y. Zhong, Xun Xu, Eberhard Klotz, “Intelligent Manufacturing in the Context of Industry 4.0: A Review,” Engineering, Elsevier, vol. 3, pp. 616–630, 2017.

X. T. Nguyen and Q. K. Luu, “Factors affecting adoption of industry 4.0 by small-and medium-sized enterprises: A case in Ho Chi Minh city, Vietnam,” Journal of Asian Finance, Economics and Business, vol. 7, no. 6, 2020, doi: 10.13106/JAFEB.2020.VOL7.NO6.255.

D. Cordero, K. L. Altamirano, J. O. Parra, and W. S. Espinoza, “Intention to Adopt Industry 4.0 by Organizations in Colombia, Ecuador, Mexico, Panama, and Peru,” IEEE Access, vol. 11, 2023, doi: 10.1109/ACCESS.2023.3238384.

V. Alcácer and V. Cruz-Machado, “Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems,” Engineering Science and Technology, an International Journal, vol. 22, no. 3, pp. 899–919, Jun. 2019, doi: 10.1016/J.JESTCH.2019.01.006.

B. Gajdzik, “Frameworks of the Maturity Model for Industry 4.0 with Assessment of Maturity Levels on the Example of the Segment of Steel Enterprises in Poland,” Journal of Open Innovation: Technology, Market, and Complexity 2022, Vol. 8, Page 77, vol. 8, no. 2, p. 77, Apr. 2022, doi: 10.3390/JOITMC8020077.

J. Chigwada, F. Mazunga, C. Nyamhere, V. Mazheke, and N. Taruvinga, “Remote poultry management system for small to medium scale producers using IoT,” Sci Afr, vol. 18, 2022, doi: 10.1016/j.sciaf.2022.e01398.

R. S. Kaplan and D. P. Norton, “The balanced scorecard: Measures That drive performance,” Harvard Business Review, vol. 83, no. 7–8. 2005.

H. L. Lee, “The triple-A supply chain,” Harv Bus Rev ., vol. 82, no. 10, pp. 102–114, 2004.

R. J. Schonberger, “World-class manufacturing: The next decade,” Ind Week, vol. 245, no. 6, 1996, doi: 10.2307/259415.

P. Belton, Competitive Strategy: Techniques for Analyzing Industries and Competitors. 2017. doi: 10.4324/9781912281060.

S.Nakajima, “Introduction to TPM: Total Productive Maintenance.pdf,” Productivity Press, Cambridge, 1988, doi: http://www.plant-maintenance.com/articles/tpm_intro.shtml.

J. Kumar and V. K. Soni, “An Exploratory Study of OEE Implementation in Indian Manufacturing Companies,” Journal of The Institution of Engineers (India): Series C, vol. 96, no. 2, 2015, doi: 10.1007/s40032-014-0153-x.

P. Gupta and S. Vardhan, “Optimizing OEE, productivity and production cost for improving sales volume in an automobile industry through TPM: A case study,” Int J Prod Res, vol. 54, no. 10, 2016, doi: 10.1080/00207543.2016.1145817.

P. G. Yazdi, A. Azizi, and M. Hashemipour, “An empirical investigation of the relationship between overall equipment efficiency (OEE) and manufacturing sustainability in industry 4.0 with time study approach,” Sustainability (Switzerland), vol. 10, no. 9, 2018, doi: 10.3390/su10093031.

S. Robledo, M. Zuluaga, L.-A. Valencia-Hernandez, O. A.-E. Arbelaez-Echeverri, P. Duque, and J.-D. Alzate-Cardona, “Tree of Science with Scopus: A Shiny Application,” Issues in Science and Technology Librarianship, no. 100, Aug. 2022, doi: 10.29173/istl2698.

A. Liberati et al., “The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration,” J Clin Epidemiol, vol. 62, no. 10, pp. e1–e34, Oct. 2009, doi: 10.1016/J.JCLINEPI.2009.06.006/ATTACHMENT/14E482F6-F614-46AB-A470-68ACBBC119FA/MMC2.DOC.

M. Baygin; H. Yetis; M. Karakose and E. Akin;, “An Effect Analysis of Industry 4.0 to Higher Education,” in 15th International Conference on Information Technology Based Higher Education and Training (ITHET), 2016. doi: 10.1109/ITHET.2016.7760744.

Becerra, L.Y., “Tecnologías de la información y las Comunicaciones en la era de la cuarta revolución industrial: Tendencias Tecnológicas y desafíos en la educación en Ingeniería,” Entre Ciencia e Ingeniería, vol. 14, no. 28, pp. 76–81, 2020.

F. Mosconi, The new European industrial policy: Global competitiveness and the manufacturing renaissance. London, England: Routledge., 2015.

L. Sommer, “Industrial revolution—Industry 4.0: Are German manufacturing SMEs the first victims of this revolution?,” Journal of Industrial Engineering and Management, vol. 8, pp. 1512-1532., 2015.

C. B. Ynzunza Cortés, J. M. Izar Landeta, J. Bocarando Chacón, Guadalupe;, F. Aguilar Pereyra, and M. Larios Osorio, “El Entorno de la Industria 4.0:Implicaciones y Perspectivas Futuras,” Conciencia Tecnológica, no. 54, 2017.

H.-D. Ma, “Internet of Things: Objectives and scientific challenges,” J. Comput. Sci. Technol., vol. 26, no. 6, pp. 919–924, 2011.

A. J. J. Cooper, “Challenges for Database Management in the Internet of Things,” IETE Technical Review, vol. 26, no. 5, pp. 320–329, 2015.

T. and H. M. Lasi, H., Fettke, P., Feld, “Industry 4.0,” Business & Information Systems Engineering, vol. 6, no. 4, pp. 239-242., 2014.

A. M. Ghaithan, Y. Alshammakhi, A. Mohammed, and K. M. Mazher, “Integrated Impact of Circular Economy, Industry 4.0, and Lean Manufacturing on Sustainability Performance of Manufacturing Firms,” Int J Environ Res Public Health, vol. 20, no. 6, 2023, doi: 10.3390/ijerph20065119.

S. I. M. and M. N. A.-K. Mostafa Al-Emran, A Survey of Internet of Things (IoT) in Education: Opportunities and Challenges, vol. 846. 2020. doi: https://doi.org/10.1007/978-3-030-24513-9_1.

S. Nižetić, P. Šolić, D. López-de-Ipiña González-de-Artaza, and L. Patrono, “Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future,” J Clean Prod, vol. 274, 2020, doi: 10.1016/j.jclepro.2020.122877.

E. Alaru, F. Puican, A. Apostu, and M. Velicanu, “Perspectives on Big Data and Big Data Analytics,” Database Systems Journal, vol. III, no. 4, 2012.

P. Trakadas et al., “An artificial intelligence-based collaboration approach in industrial iot manufacturing: Key concepts, architectural extensions and potential applications,” Sensors (Switzerland), vol. 20, no. 19, 2020, doi: 10.3390/s20195480.

B. hu Li, B. cun Hou, W. tao Yu, X. bing Lu, and C. wei Yang, “Applications of artificial intelligence in intelligent manufacturing: a review,” Frontiers of Information Technology and Electronic Engineering, vol. 18, no. 1. 2017. doi: 10.1631/FITEE.1601885.

D. Jones, C. Snider, A. Nassehi, J. Yon, and B. Hicks, “Characterising the Digital Twin: A systematic literature review,” CIRP J Manuf Sci Technol, vol. 29, 2020, doi: 10.1016/j.cirpj.2020.02.002.

A. M. Turing, “Computing machinery and intelligence,” in Machine Intelligence: Perspectives on the Computational Model, 2012. doi: 10.1525/9780520318267-013.

S. W. Kim, J. H. Kong, S. W. Lee, and S. Lee, “Recent Advances of Artificial Intelligence in Manufacturing Industrial Sectors: A Review,” International Journal of Precision Engineering and Manufacturing, vol. 23, no. 1. 2022. doi: 10.1007/s12541-021-00600-3.

M. Grieves, “Digital Twin : Manufacturing Excellence through Virtual Factory Replication,” White Paper, no. March, 2014.

E. a Lee, “Cyber Physical Systems : Design Challenges University of California , Berkeley,” Distrib Comput, 2008, doi: 10.1109/ISORC.2008.25.

A. A. Letichevsky, O. O. Letychevskyi, V. G. Skobelev, and V. A. Volkov, “Cyber-Physical Systems,” Cybern Syst Anal, vol. 53, no. 6, 2017, doi: 10.1007/s10559-017-9984-9.

A. Kusiak, “Service manufacturing: Basic concepts and technologies,” J Manuf Syst, vol. 52, 2019, doi: 10.1016/j.jmsy.2019.07.002.

A. Kusiak, “Smart manufacturing,” Int J Prod Res, vol. 56, no. 1–2, 2018, doi: 10.1080/00207543.2017.1351644.

S. Liang, M. Rajora, X. Liu, C. Yue, P. Zou, and L. Wang, “Intelligent manufacturing systems: A review,” International Journal of Mechanical Engineering and Robotics Research, vol. 7, no. 3. 2018. doi: 10.18178/ijmerr.7.3.324-330.

S. M. Párraga Franco, N. F. Pinargote Vázquez, C. M. García Álava, and J. C. Zamora Sornoza, “Indicadores de gestión financiera en pequeñas y medianas empresas en Iberoamérica: una revisión sistemática.,” Dilemas contemporáneos: Educación, Política y Valores, 2021, doi: 10.46377/dilemas.v8i.2610.

M. E. Porter, Competitive Advantage: Creating and Sustaining Superior Performance, vol. Fir Free P, no. 1. 1998. doi: 10.1016/j.neubiorev.2009.11.015.

H. Ore, “Planeamiento estratégico como instrumento de gestión en las empresas: Revisión bibliográfica,” Revista Científica Pakamuros, vol. 8, no. 4, 2020, doi: 10.37787/pakamuros-unj.v8i4.147.

L. H. Morris Molina, “Entre Ingeniería, Tecnología y Productividad,” Entre ciencia e ingeniería, vol. 14, no. 28, 2020, doi: 10.31908/19098367.1849.

F. Hernández Centeno and W. Sifuentes Huayanay, “Lean Manufacturing: Literature review and implementation analysis,” Journal of Scientific and Technological Research Industrial, vol. 3, no. 2, 2022, doi: 10.47422/jstri.v3i2.29.

K. Foit, G. Gołda, and A. Kampa, “Integration and Evaluation of Intra-Logistics Processes in Flexible Production Systems Based on OEE Metrics, with the Use of Computer Modelling and Simulation of AGVs,” Processes 2020, Vol. 8, Page 1648, vol. 8, no. 12, p. 1648, Dec. 2020, doi: 10.3390/PR8121648.

Z. F. Hunusalela et al., “Productivity tool for automated guided vehicles: OEE indicator perspective,” IOP Conf Ser Mater Sci Eng, vol. 1193, no. 1, p. 012113, Oct. 2021, doi: 10.1088/1757-899X/1193/1/012113.

J. Zhou, Y. Wang, and Y. Q. Chua, “Real-Time OEE for Industry 4.0 Learning and Practice Training,” SSRN Electronic Journal, Jun. 2021, doi: 10.2139/SSRN.3864886.

T. C. Ng, S. Y. Lau, M. Ghobakhloo, M. Fathi, and M. S. Liang, “The Application of Industry 4.0 Technological Constituents for Sustainable Manufacturing: A Content-Centric Review,” Sustainability 2022, Vol. 14, Page 4327, vol. 14, no. 7, p. 4327, Apr. 2022, doi: 10.3390/SU14074327.

G. Tsaramirsis et al., “A Modern Approach towards an Industry 4.0 Model: From Driving Technologies to Management,” J Sens, vol. 2022, 2022, doi: 10.1155/2022/5023011.

O. Rodríguez-Espíndola, S. Chowdhury, P. K. Dey, P. Albores, and A. Emrouznejad, “Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing,” Technol Forecast Soc Change, vol. 178, May 2022, doi: 10.1016/J.TECHFORE.2022.121562.

A. Reiman, J. Kaivo-oja, E. Parviainen, E. P. Takala, and T. Lauraeus, “Human factors and ergonomics in manufacturing in the industry 4.0 context – A scoping review,” Technol Soc, vol. 65, p. 101572, May 2021, doi: 10.1016/J.TECHSOC.2021.101572.

M. Javaid, A. Haleem, R. P. Singh, and R. Suman, “Enabling flexible manufacturing system (FMS) through the applications of industry 4.0 technologies,” Internet of Things and Cyber-Physical Systems, vol. 2, pp. 49–62, 2022, doi: 10.1016/J.IOTCPS.2022.05.005.

Muhammad Imran Majid, Ejaz Malik, Tahniyat Aslam, Osama Mahfooz, and Fatima Maqbool, “Design and Implementation of Low-Cost Data Acquisition System for Small and Medium Enterprises (SMEs) of Pakistan,” Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences, vol. 59, no. 4, pp. 13–23, Nov. 2022, doi: 10.53560/PPASA(59-4)784.

R. Rosati et al., “From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0,” J Intell Manuf, vol. 34, no. 1, pp. 107–121, Jan. 2023, doi: 10.1007/S10845-022-01960-X.

İ. Gerekli, T. Z. Çelik, and İ. Bozkurt, “Industry 4.0 and Smart Production,” TEM Journal, vol. 10, no. 2, pp. 799–805, May 2021, doi: 10.18421/TEM102-37.

M. Javaid, Abid Haleem, R. Pratap Singh, S. Rab, and R. Suman, “Upgrading the manufacturing sector via applications of Industrial Internet of Things (IIoT),” Sensors International, vol. 2, Jan. 2021, doi: 10.1016/J.SINTL.2021.100129.

S. Kahveci, B. Alkan, M. H. Ahmad, B. Ahmad, and R. Harrison, “An end-to-end big data analytics platform for IoT-enabled smart factories: A case study of battery module assembly system for electric vehicles,” J Manuf Syst, vol. 63, pp. 214–223, Apr. 2022, doi: 10.1016/J.JMSY.2022.03.010.

T. Sarı, H. K. Güleş, and B. Yiğitol, “Awareness and readiness of Industry 4.0: The case of Turkish manufacturing industry,” Advances in Production Engineering And Management, vol. 15, no. 1, pp. 57–68, Mar. 2020, doi: 10.14743/APEM2020.1.349.

Y. El Kihel, A. Zouggar Amrani, Y. Ducq, D. Amegouz, and A. Lfakir, “Methodology combining industry 4.0 technologies and KPI’s reliability for supply chain performance,” Int J Comput Integr Manuf, 2023, doi: 10.1080/0951192X.2022.2162605.

S. Konur, Y. Lan, D. Thakker, G. Morkyani, N. Polovina, and J. Sharp, “Towards design and implementation of Industry 4.0 for food manufacturing,” Neural Comput Appl, 2021, doi: 10.1007/S00521-021-05726-Z.

F. M. Somohano-Rodríguez and A. Madrid-Guijarro, “Do industry 4.0 technologies improve Cantabrian manufacturing smes performance? The role played by industry competition,” Technol Soc, vol. 70, Aug. 2022, doi: 10.1016/J.TECHSOC.2022.102019.

G. Bortoluzzi, M. Chiarvesio, R. Romanello, R. Tabacco, and V. Veglio, “Servitisation and performance in the business-to-business context: the moderating role of Industry 4.0 technologies,” Journal of Manufacturing Technology Management, vol. 33, no. 9, pp. 108–128, 2022, doi: 10.1108/JMTM-08-2021-0317.

M. S. B. Abd Rahman, E. Mohamad, and A. A. B. Abdul Rahman, “Development of IoT—enabled data analytics enhance decision support system for lean manufacturing process improvement,” Concurr Eng Res Appl, vol. 29, no. 3, pp. 208–220, 2021, doi: 10.1177/1063293X20987911.

F. khan Fasuludeen Kunju, N. Naveed, M. N. Anwar, and M. I. Ul Haq, “Production and maintenance in industries: impact of industry 4.0,” Industrial Robot, vol. 49, no. 3, pp. 461–475, Apr. 2022, doi: 10.1108/IR-09-2021-0211.

G. C. Zutin, G. F. Barbosa, P. C. de Barros, E. B. Tiburtino, F. L. F. Kawano, and S. B. Shiki, “Readiness levels of Industry 4.0 technologies applied to aircraft manufacturing—a review, challenges and trends,” International Journal of Advanced Manufacturing Technology, vol. 120, no. 1–2, pp. 927–943, May 2022, doi: 10.1007/S00170-022-08769-1.

S. Hamdan, S. Almajali, M. Ayyash, H. Bany Salameh, and Y. Jararweh, “An intelligent edge-enabled distributed multi-task learning architecture for large-scale IoT-based cyber–physical systems,” Simul Model Pract Theory, vol. 122, p. 102685, Jan. 2023, doi: 10.1016/J.SIMPAT.2022.102685.

R. Črešnar, M. Dabić, N. Stojčić, and Z. Nedelko, “It takes two to tango: technological and non-technological factors of Industry 4.0 implementation in manufacturing firms,” Review of Managerial Science, Apr. 2022, doi: 10.1007/S11846-022-00543-7.

A. Verma, A. Goyal, S. Kumara, and T. Kurfess, “Edge-cloud computing performance benchmarking for IoT based machinery vibration monitoring,” Manuf Lett, vol. 27, pp. 39–41, Jan. 2021, doi: 10.1016/J.MFGLET.2020.12.004.

S. V. Lakshmi, J. Janet, P. K. Rani, K. Sujatha, K. Satyamoorthy, and S. Marichamy, “Role and applications of IoT in materials and manufacturing industries – Review,” Mater Today Proc, vol. 45, pp. 2925–2928, Jan. 2021, doi: 10.1016/J.MATPR.2020.11.939.

H. Yang, S. Kumara, S. T. S. Bukkapatnam, and F. Tsung, “The internet of things for smart manufacturing: A review,” IISE Trans, vol. 51, no. 11, pp. 1190–1216, Nov. 2019, doi: 10.1080/24725854.2018.1555383.

S. Wadhwa, S. Rani, Kavita, S. Verma, J. Shafi, and M. Wozniak, “Energy Efficient Consensus Approach of Blockchain for IoT Networks with Edge Computing,” Sensors 2022, Vol. 22, Page 3733, vol. 22, no. 10, p. 3733, May 2022, doi: 10.3390/S22103733.

M. Ammar, A. Haleem, M. Javaid, S. Bahl, and A. S. Verma, “Implementing Industry 4.0 technologies in self-healing materials and digitally managing the quality of manufacturing,” Mater Today Proc, vol. 52, pp. 2285–2294, Jan. 2022, doi: 10.1016/J.MATPR.2021.09.248.

M. M. Sadeeq, N. M. Abdulkareem, S. R. M. Zeebaree, D. M. Ahmed, A. S. Sami, and R. R. Zebari, “IoT and Cloud Computing Issues, Challenges and Opportunities: A Review,” Qubahan Academic Journal, vol. 1, no. 2, pp. 1–7, Mar. 2021, doi: 10.48161/QAJ.V1N2A36.

F. S. Costa et al., “Fasten iiot: An open real-time platform for vertical, horizontal and end-to-end integration,” Sensors (Switzerland), vol. 20, no. 19, pp. 1–25, Oct. 2020, doi: 10.3390/S20195499.

J. Stanke, M. Unterberg, D. Trauth, and T. Bergs, “Development of a hybrid DLT cloud architecture for the automated use of finite element simulation as a service for fine blanking,” International Journal of Advanced Manufacturing Technology, vol. 108, no. 11–12, pp. 3717–3724, Jun. 2020, doi: 10.1007/S00170-020-05567-5.

V. A. Nunes and G. F. Barbosa, “Simulation-based analysis of AGV workload used on aircraft manufacturing system: A theoretical approach,” Acta Scientiarum - Technology, vol. 42, no. 1, 2020, doi: 10.4025/ACTASCITECHNOL.V42I1.47034.

T. Coito et al., “Integration of industrial IoT architectures for dynamic scheduling,” Comput Ind Eng, vol. 171, p. 108387, Sep. 2022, doi: 10.1016/J.CIE.2022.108387.

S. Pasika and S. T. Gandla, “Smart water quality monitoring system with cost-effective using IoT,” Heliyon, vol. 6, no. 7, p. e04096, Jul. 2020, doi: 10.1016/J.HELIYON.2020.E04096.

P. Pop et al., “The FORA Fog Computing Platform for Industrial IoT,” Inf Syst, vol. 98, p. 101727, May 2021, doi: 10.1016/J.IS.2021.101727.

A. A. B. Junior and M. J. Carrer, “Adoption of Industry 4.0 technologies: an analysis of small and medium-sized companies in the state of São Paulo, Brazil,” Gestão & Produção, vol. 29, p. e122, Nov. 2022, doi: 10.1590/1806-9649-2022V29E122.

T. Sutikno and D. Thalmann, “Insights on the internet of things: past, present, and future directions,” Telkomnika (Telecommunication Computing Electronics and Control), vol. 20, no. 6, 2022, doi: 10.12928/TELKOMNIKA.v20i6.22028.

R. Contreras-Masse, A. Ochoa-Zezzatti, V. García, L. Pérez-Dominguez, and M. Elizondo-Cortés, “Implementing a novel use of multicriteria decision analysis to select iiot platforms for smart manufacturing,” Symmetry (Basel), vol. 12, no. 3, Mar. 2020, doi: 10.3390/SYM12030368.

M. Fahmideh and D. Zowghi, “An Exploration of IoT Platform Development,” Inf Syst, vol. 87, Apr. 2020, doi: 10.1016/j.is.2019.06.005.

M. J. Beliatis, K. Jensen, L. Ellegaard, A. Aagaard, and M. Presser, “Next Generation Industrial IoT Digitalization for Traceability in Metal Manufacturing Industry: A Case Study of Industry 4.0,” Electronics 2021, Vol. 10, Page 628, vol. 10, no. 5, p. 628, Mar. 2021, doi: 10.3390/ELECTRONICS10050628.

R. Gadekar, B. Sarkar, and A. Gadekar, “Key performance indicator based dynamic decision-making framework for sustainable Industry 4.0 implementation risks evaluation: reference to the Indian manufacturing industries,” Ann Oper Res, vol. 318, no. 1, pp. 189–249, Nov. 2022, doi: 10.1007/S10479-022-04828-8.

A. Aljinović, N. Gjeldum, B. Bilić, and M. Mladineo, “Optimization of industry 4.0 implementation selection process towards enhancement of a manual assembly line,” Energies (Basel), vol. 15, no. 1, Jan. 2022, doi: 10.3390/EN15010030.

A. Martikkala, B. Mayanti, P. Helo, A. Lobov, and I. F. Ituarte, “Smart textile waste collection system - Dynamic route optimization with IoT,” J Environ Manage, vol. 335, Jun. 2023, doi: 10.1016/J.JENVMAN.2023.117548.

V. Pandey, A. Sircar, N. Bist, K. Solanki, and K. Yadav, “Accelerating the renewable energy sector through Industry 4.0: Optimization opportunities in the digital revolution,” International Journal of Innovation Studies, vol. 7, no. 2, pp. 171–188, Jun. 2023, doi: 10.1016/J.IJIS.2023.03.003.

S. Nahavandi, “INDUSTRY 5 . 0 definition,” Sustainability, vol. 11, 2019.

P. Kumar, J. Bhamu, and K. S. Sangwan, “Analysis of Barriers to Industry 4.0 adoption in Manufacturing Organizations: An ISM Approach,” Procedia CIRP, vol. 98, pp. 85–90, 2021, doi: 10.1016/J.PROCIR.2021.01.010.

Y. Fernando, I. S. Ika, A. Gui, R. B. Ikhsan, F. Mergeresa, and Y. Ganesan, “A mixed-method study on the barriers of industry 4.0 adoption in the Indonesian SMEs manufacturing supply chains,” Journal of Science and Technology Policy Management, vol. ahead-of-print, no. ahead-of-print, 2022, doi: 10.1108/JSTPM-10-2021-0155/FULL/XML.

A. Raj, G. Dwivedi, A. Sharma, A. B. Lopes de Sousa Jabbour, and S. Rajak, “Barriers to the adoption of industry 4.0 technologies in the manufacturing sector: An inter-country comparative perspective,” Int J Prod Econ, vol. 224, p. 107546, Jun. 2020, doi: 10.1016/j.ijpe.2019.107546.

S. Kumar, R. D. Raut, E. Aktas, B. E. Narkhede, and V. V. Gedam, “Barriers to adoption of industry 4.0 and sustainability: a case study with SMEs,” Int J Comput Integr Manuf, 2022, doi: 10.1080/0951192X.2022.2128217/SUPPL_FILE/TCIM_A_2128217_SM1706.DOCX.

X. T. Nguyen and Q. K. Luu, “Factors affecting adoption of industry 4.0 by small-and medium-sized enterprises: A case in Ho Chi Minh city, Vietnam,” Journal of Asian Finance, Economics and Business, vol. 7, no. 6, pp. 255–264, 2020, doi: 10.13106/JAFEB.2020.VOL7.NO6.255.

F. Rosin, P. Forget, S. Lamouri, and R. Pellerin, “Enhancing the Decision-Making Process through Industry 4.0 Technologies,” Sustainability (Switzerland), vol. 14, no. 1, Jan. 2022, doi: 10.3390/SU14010461.

N. Pappas, A. Caputo, M. M. Pellegrini, G. Marzi, and E. Michopoulou, “The complexity of decision-making processes and IoT adoption in accommodation SMEs,” J Bus Res, vol. 131, pp. 573–583, Jul. 2021, doi: 10.1016/J.JBUSRES.2021.01.010.

G. Nota, F. D. Nota, D. Peluso, and A. T. Lazo, “Energy efficiency in Industry 4.0: The case of batch production processes,” Sustainability (Switzerland), vol. 12, no. 16, 2020, doi: 10.3390/su12166631.

L. Morris, A. Toro, L. Becerra, M. Granda, and M. Cardona, “MAPPING FOR THE STRENGTHENING OF PRODUCTIVE CAPACITIES IN TERMS OF PRODUCTIVITY INDICATORS OF THE METALWORKING SECTOR IN RISARALDA, COLOMBIA,” in Proceedings from the International Congress on Project Management and Engineering, 2022.

Z. M. Çınar, Q. Zeeshan, and O. Korhan, “A framework for industry 4.0 readiness and maturity of smart manufacturing enterprises: A case study,” Sustainability (Switzerland), vol. 13, no. 12, Jun. 2021, doi: 10.3390/SU13126659.

F. M. Abdullah, A. M. Al-Ahmari, and S. Anwar, “Analyzing Interdependencies among Influencing Factors in Smart Manufacturing,” Sustainability (Switzerland), vol. 15, no. 4, Feb. 2023, doi: 10.3390/SU15043864.

S. R. Bin Rahamaddulla, Z. Leman, B. T. H. T. Bin Baharudin, and S. A. Ahmad, “Conceptualizing smart manufacturing readiness-maturity model for small and medium enterprise (Sme) in malaysia,” Sustainability (Switzerland), vol. 13, no. 17, Sep. 2021, doi: 10.3390/SU13179793.

G. S. Kim and Y. H. Lee, “Transformation towards a smart maintenance factory: The case of a vessel maintenance depot,” Machines, vol. 9, no. 11, Nov. 2021, doi: 10.3390/MACHINES9110267.

Publicado
2024-07-01
Cómo citar
Becerra Sánchez, line, Herrera Arroyave, J., Morris Molina, L. H., & Toro Lazo, A. (2024). Tecnologías de la cuarta revolución industrial utilizadas en la manufactura para mejorar los indicadores de productividad: Una revisión. Entre Ciencia E Ingeniería, 18(35), 46-58. https://doi.org/10.31908/19098367.3149
Número
Vol. 18 Núm. 35 (2024)
Sección
Artículos
Derechos de autor 2024 Entre Ciencia e Ingeniería