Component-Based microservices for flexible and scalable automation of industrial bioprocesses
Industry 4.0 involves the digital transformation of the industry with the integration and digitization of all industrial processes that make up the value chain, which is characterized by adaptability, flexibility, and efficiency to meet the needs of customers in today’s market. Therefore, the adapta...
- Autores:
-
Ibarra-Junquera, Vrani
González, Apolinar
Paredes, Carlos Mario
Martínez Castro, Diego
Nuñez, Rubi
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2021
- Institución:
- Universidad Autónoma de Occidente
- Repositorio:
- RED: Repositorio Educativo Digital UAO
- Idioma:
- eng
- OAI Identifier:
- oai:red.uao.edu.co:10614/13891
- Acceso en línea:
- https://hdl.handle.net/10614/13891
https://red.uao.edu.co/
- Palabra clave:
- Automatización industrial
Industry 4.0
Distributed industrial automation systems,
Interoperability
Middleware
Industrial cyber-physical systems
- Rights
- openAccess
- License
- Derechos Reservados IEEE Access, 2021
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Component-Based microservices for flexible and scalable automation of industrial bioprocesses |
| title |
Component-Based microservices for flexible and scalable automation of industrial bioprocesses |
| spellingShingle |
Component-Based microservices for flexible and scalable automation of industrial bioprocesses Automatización industrial Industry 4.0 Distributed industrial automation systems, Interoperability Middleware Industrial cyber-physical systems |
| title_short |
Component-Based microservices for flexible and scalable automation of industrial bioprocesses |
| title_full |
Component-Based microservices for flexible and scalable automation of industrial bioprocesses |
| title_fullStr |
Component-Based microservices for flexible and scalable automation of industrial bioprocesses |
| title_full_unstemmed |
Component-Based microservices for flexible and scalable automation of industrial bioprocesses |
| title_sort |
Component-Based microservices for flexible and scalable automation of industrial bioprocesses |
| dc.creator.fl_str_mv |
Ibarra-Junquera, Vrani González, Apolinar Paredes, Carlos Mario Martínez Castro, Diego Nuñez, Rubi |
| dc.contributor.author.none.fl_str_mv |
Ibarra-Junquera, Vrani González, Apolinar Paredes, Carlos Mario Martínez Castro, Diego Nuñez, Rubi |
| dc.subject.spa.fl_str_mv |
Automatización industrial |
| topic |
Automatización industrial Industry 4.0 Distributed industrial automation systems, Interoperability Middleware Industrial cyber-physical systems |
| dc.subject.proposal.eng.fl_str_mv |
Industry 4.0 Distributed industrial automation systems, Interoperability Middleware Industrial cyber-physical systems |
| description |
Industry 4.0 involves the digital transformation of the industry with the integration and digitization of all industrial processes that make up the value chain, which is characterized by adaptability, flexibility, and efficiency to meet the needs of customers in today’s market. Therefore, the adaptations of the new bioprocess industry require a lot of flexibility to react quickly and constantly to market changes and to be able to offer more specialized, customized products with high operational efficiency. This paper presents a flexible, scalable, and robust framework based on software components, container technology, microservice concepts, and the publish/subscribe paradigm. This framework allows new components to be added or removed online, without the need for system reconfiguration, while maintaining temporal and functional constraints in industrial automation systems. The main objective of the framework proposed is the use of components based on microservices, allowing easy implementation, scalability, and fast maintenance, without losing or degrading the robustness from previous developments. Finally, the effectiveness of the proposed framework was verified in two case studies (1) a soursop soda making process is presented, with a fuzzy controller implemented to keep the pasteurizer output flow constant (UHT) and (2) an automatic storage tank selection and filling process with actuated valves to direct the fluid to the corresponding tank at the time to start the process. The results showed that the platform provided a high-fidelity design, analysis, and testing environment for the flow of cyber information and its effect on the physical operation in a beverage processing plant with high demand for flexibility, scalability, and robustness of its processes, as they were experimentally verified in a real production process |
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2021 |
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2021-04 |
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2022-05-19T14:33:01Z |
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2022-05-19T14:33:01Z |
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Artículo de revista |
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Repositorio Educativo Digital |
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9 |
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Junquera, V. I., González Potes, A., Paredes, C. M., Martínez Castro, D., Nuñez Vizcaino, R. A. (2021). Component-based microservices for flexible and scalable automation of industrial bioprocesses. IEEE. IEEE Access. Vol. 9, pp. 58192- 58207. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9399423&tag=1 |
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IEEE Access |
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[1] O. Cardin, ``Classi cation of cyber-physical production systems applications: Proposition of an analysis framework,'' Comput. Ind., vol. 104, pp. 11 21, Jan. 2019. [2] I. Ungurean and N. C. Gaitan, ``A software architecture for the industrial Internet of Things A conceptual model,'' Sensors, vol. 20, no. 19, pp. 1 19, 2020. [3] W. Z. Khan, E. Ahmed, S. Hakak, I. Yaqoob, and A. Ahmed, ``Edge computing: A survey,'' Future Gener. Comput. Syst., vol. 97, pp. 219 235, Aug. 2019. [4] S. Aheleroff, X. Xu, Y. Lu, M. Aristizabal, J. P. Velásquez, B. Joa, and Y. Valencia, ``IoT-enabled smart appliances under industry 4.0: A case study,'' Adv. Eng. Informat., vol. 43, Jan. 2020, Art. no. 101043. [5] B. Chen, J. Wan, L. Shu, P. Li, M. Mukherjee, and B. Yin, ``Smart factory of industry 4.0: Key technologies, application case, and challenges,'' IEEE Access, vol. 6, pp. 6505 6519, 2018. [6] W. Dai, P. Wang, W. Sun, X. Wu, H. Zhang, V. Vyatkin, and G. Yang, “Semantic integration of plug-and-play software components for industrial edges based on microservices,” IEEE Access, vol. 7, pp. 125882 125892, 2019. [7] M. Alam, J. Ru no, J. Ferreira, S. H. Ahmed, N. Shah, and Y. Chen, ``Orchestration of microservices for IoT using docker and edge computing,'' IEEE Commun. Mag., vol. 56, no. 9, pp. 118 123, Sep. 2018. [8] R. P. Pontarolli, J. A. Bigheti, M. M. Fernandes, F. O. Domingues, S. L. Risso, and E. P. Godoy, ``Microservice orchestration for process control in industry 4.0,'' in Proc. IEEE Int. Workshop Metrol. Ind. 4.0 IoT, Jun. 2020, pp. 245 249. [9] A. Benayache, A. Bilami, S. Barkat, P. Lorenz, and H. Taleb, ``MsM: A microservice middleware for smart WSN-based IoT application,'' J. Netw. Comput. Appl., vol. 144, pp. 138 154, Oct. 2019. [10] M. Krämer, S. Frese, and A. Kuijper, ``Implementing secure applications in smart city clouds using microservices,'' Future Gener. Comput. Syst., vol. 99, pp. 308 320, Oct. 2019. [11] W. Dai, P. Zhou, D. Zhao, S. Lu, and T. Chai, ``Hardware-in-the-loop simulation platform for supervisory control of mineral grinding process,'' Powder Technol., vol. 288, pp. 422 434, Jan. 2016. [12] W. Dai, G. Huang, F. Chu, and T. Chai, ``Con gurable platform for optimal-setting control of grinding processes,'' IEEE Access, vol. 5, pp. 26722 26733, 2017. [13] F. Januario, A. Cardoso, and P. Gil, ``A distributed multi-agent framework for resilience enhancement in cyber-physical systems,'' IEEE Access, vol. 7, pp. 31342 31357, 2019. [14] T. Goldschmidt, S. Hauck-Stattelmann, S. Malakuti, and S. Grüner, ``Container-based architecture for exible industrial control applications,'' J. Syst. Archit., vol. 84, pp. 28 36, Mar. 2018. [15] F. Hofer, M. A. Sehr, A. Sangiovanni-Vincentelli, and B. Russo, ``Industrial control via application containers: Maintaining determinism in IAAS,'' 2020, arXiv:2005.01890. [Online]. Available: https://arxiv. org/abs/2005.01890 [16] P. González-Nalda, I. Etxeberria-Agiriano, I. Calvo, and M. C. Otero, ``A modular CPS architecture design based on ROS and docker,'' Int. J. Interact. Des. Manuf., vol. 11, no. 4, pp. 949 955, Nov. 2017. [17] X. Wan, X. Guan, T. Wang, G. Bai, and B.-Y. Choi, ``Application deployment using microservice and docker containers: Framework and optimization,'' J. Netw. Comput. Appl., vol. 119, pp. 97 109, Oct. 2018. [18] L. Abeni, A. Balsini, and T. Cucinotta, ``Container-based real-time scheduling in the linux kernel,'' ACM SIGBED Rev., vol. 16, no. 3, pp. 33 38, Nov. 2019. [19] T. Caraza-Harter and M. M. Swift, Blending Containers and Virtual Machines: A Study of Firecracker and Gvisor. New York, NY, USA: Association for Computing Machinery, 2020. [20] Z. Kozhirbayev and R. O. Sinnott, ``A performance comparison of container-based technologies for the cloud,'' Future Gener. Comput. Syst., vol. 68, pp. 175 182, Mar. 2017. [21] H. L. Ren and Y. P. Jiao, ``Study on the distributed real-time and embedded system middleware based on the DDS,'' Adv. Mater. Res., vols. 433 440, pp. 7522 7525, Feb. 2012. [22] B. Almadani and S. M. Mostafa, ``IIoT based multimodal communication model for agriculture and agro-industries,'' IEEE Access, vol. 9, pp. 10070 10088, 2021. [23] M. El Hariri, T. Youssef, M. Saleh, S. Faddel, H. Habib, and O. A. Mohammed, ``Aframework for analyzing and testing cyber physical interactions for smart grid applications,'' Electronics, vol. 8, no. 12, p. 1455, Dec. 2019. [24] I. Ungurean, N. C. Gaitan, and V. G. Gaitan, ``A middleware based architecture for the industrial Internet of Things,'' KSII Trans. Internet Inf. Syst., vol. 10, no. 7, pp. 2874 2891, 2016. [25] T. Coito, M. S. E. Martins, J. L. Viegas, B. Firme, J. Figueiredo, S. M. Vieira, and J. M. C. Sousa, ``A middleware platform for intelligent automation: An industrial prototype implementation,'' Comput. Ind., vol. 123, Dec. 2020, Art. no. 103329. [26] R. Beregi, G. Pedone, and I. Mezgár, ``A novel uid architecture for cyberphysical production systems,'' Int. J. Comput. Integr. Manuf., vol. 32, nos. 4 5, pp. 340 351, May 2019. [27] G. Chen, P. Wang, B. Feng, Y. Li, and D. Liu, ``The framework design of smart factory in discrete manufacturing industry based on cyber-physical system,'' Int. J. Comput. Integr. Manuf., vol. 33, no. 1, pp. 79 101, Jan. 2020. [28] M. Merdan, T. Hoebert, E. List, and W. Lepuschitz, ``Knowledge-based cyber-physical systems for assembly automation,'' Prod. Manuf. Res., vol. 7, no. 1, pp. 223 254, Jan. 2019. [29] A. González-Potes, W. A. Mata-López, V. Ibarra-Junquera, A. M. Ochoa-Brust, D. Martínez-Castro, and A. Crespo, ``Distributed multi-agent architecture for real-time wireless control networks of multiple plants,'' Eng. Appl. Artif. Intell., vol. 56, pp. 142 156, Nov. 2016. [30] G. M. Kurtzer, V. Sochat, and M. W. Bauer, ``Singularity: Scienti c containers for mobility of compute,'' PLoS ONE, vol. 12, no. 5, May 2017, Art. no. e0177459. |
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Ibarra-Junquera, Vrani775c0fcd76dad13f53399833b2132d2aGonzález, Apolinarc71d2127efe309f1c72ed360a78af749Paredes, Carlos Mario13e0d405db634d5a5e2f79d519b07faeMartínez Castro, Diegovirtual::2998-1Nuñez, Rubif8efd36590332a3256c4742de3c933792022-05-19T14:33:01Z2022-05-19T14:33:01Z2021-0421693536https://hdl.handle.net/10614/13891Universidad Autónoma de OccidenteRepositorio Educativo Digitalhttps://red.uao.edu.co/Industry 4.0 involves the digital transformation of the industry with the integration and digitization of all industrial processes that make up the value chain, which is characterized by adaptability, flexibility, and efficiency to meet the needs of customers in today’s market. Therefore, the adaptations of the new bioprocess industry require a lot of flexibility to react quickly and constantly to market changes and to be able to offer more specialized, customized products with high operational efficiency. This paper presents a flexible, scalable, and robust framework based on software components, container technology, microservice concepts, and the publish/subscribe paradigm. This framework allows new components to be added or removed online, without the need for system reconfiguration, while maintaining temporal and functional constraints in industrial automation systems. The main objective of the framework proposed is the use of components based on microservices, allowing easy implementation, scalability, and fast maintenance, without losing or degrading the robustness from previous developments. Finally, the effectiveness of the proposed framework was verified in two case studies (1) a soursop soda making process is presented, with a fuzzy controller implemented to keep the pasteurizer output flow constant (UHT) and (2) an automatic storage tank selection and filling process with actuated valves to direct the fluid to the corresponding tank at the time to start the process. The results showed that the platform provided a high-fidelity design, analysis, and testing environment for the flow of cyber information and its effect on the physical operation in a beverage processing plant with high demand for flexibility, scalability, and robustness of its processes, as they were experimentally verified in a real production process16 páginasapplication/pdfengIEEE AccessDerechos Reservados IEEE Access, 2021https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_abf2https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9399423&tag=1Automatización industrialIndustry 4.0Distributed industrial automation systems,InteroperabilityMiddlewareIndustrial cyber-physical systemsComponent-Based microservices for flexible and scalable automation of industrial bioprocessesArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a8558207581929Junquera, V. I., González Potes, A., Paredes, C. M., Martínez Castro, D., Nuñez Vizcaino, R. A. (2021). Component-based microservices for flexible and scalable automation of industrial bioprocesses. IEEE. IEEE Access. Vol. 9, pp. 58192- 58207. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9399423&tag=1IEEE Access[1] O. Cardin, ``Classi cation of cyber-physical production systems applications: Proposition of an analysis framework,'' Comput. Ind., vol. 104, pp. 11 21, Jan. 2019.[2] I. Ungurean and N. C. Gaitan, ``A software architecture for the industrial Internet of Things A conceptual model,'' Sensors, vol. 20, no. 19, pp. 1 19, 2020.[3] W. Z. Khan, E. Ahmed, S. Hakak, I. Yaqoob, and A. Ahmed, ``Edge computing: A survey,'' Future Gener. Comput. Syst., vol. 97, pp. 219 235, Aug. 2019.[4] S. Aheleroff, X. Xu, Y. Lu, M. Aristizabal, J. P. Velásquez, B. Joa, and Y. Valencia, ``IoT-enabled smart appliances under industry 4.0: A case study,'' Adv. Eng. Informat., vol. 43, Jan. 2020, Art. no. 101043.[5] B. Chen, J. Wan, L. Shu, P. Li, M. Mukherjee, and B. Yin, ``Smart factory of industry 4.0: Key technologies, application case, and challenges,'' IEEE Access, vol. 6, pp. 6505 6519, 2018.[6] W. Dai, P. Wang, W. Sun, X. Wu, H. Zhang, V. Vyatkin, and G. Yang, “Semantic integration of plug-and-play software components for industrial edges based on microservices,” IEEE Access, vol. 7, pp. 125882 125892, 2019.[7] M. Alam, J. Ru no, J. Ferreira, S. H. Ahmed, N. Shah, and Y. Chen, ``Orchestration of microservices for IoT using docker and edge computing,'' IEEE Commun. Mag., vol. 56, no. 9, pp. 118 123, Sep. 2018.[8] R. P. Pontarolli, J. A. Bigheti, M. M. Fernandes, F. O. Domingues, S. L. Risso, and E. P. Godoy, ``Microservice orchestration for process control in industry 4.0,'' in Proc. IEEE Int. Workshop Metrol. Ind. 4.0 IoT, Jun. 2020, pp. 245 249.[9] A. Benayache, A. Bilami, S. Barkat, P. Lorenz, and H. Taleb, ``MsM: A microservice middleware for smart WSN-based IoT application,'' J. Netw. Comput. Appl., vol. 144, pp. 138 154, Oct. 2019.[10] M. Krämer, S. Frese, and A. Kuijper, ``Implementing secure applications in smart city clouds using microservices,'' Future Gener. Comput. Syst., vol. 99, pp. 308 320, Oct. 2019.[11] W. Dai, P. Zhou, D. Zhao, S. Lu, and T. Chai, ``Hardware-in-the-loop simulation platform for supervisory control of mineral grinding process,'' Powder Technol., vol. 288, pp. 422 434, Jan. 2016.[12] W. Dai, G. Huang, F. Chu, and T. Chai, ``Con gurable platform for optimal-setting control of grinding processes,'' IEEE Access, vol. 5, pp. 26722 26733, 2017.[13] F. Januario, A. Cardoso, and P. Gil, ``A distributed multi-agent framework for resilience enhancement in cyber-physical systems,'' IEEE Access, vol. 7, pp. 31342 31357, 2019.[14] T. Goldschmidt, S. Hauck-Stattelmann, S. Malakuti, and S. Grüner, ``Container-based architecture for exible industrial control applications,'' J. Syst. Archit., vol. 84, pp. 28 36, Mar. 2018.[15] F. Hofer, M. A. Sehr, A. Sangiovanni-Vincentelli, and B. Russo, ``Industrial control via application containers: Maintaining determinism in IAAS,'' 2020, arXiv:2005.01890. [Online]. Available: https://arxiv. org/abs/2005.01890[16] P. González-Nalda, I. Etxeberria-Agiriano, I. Calvo, and M. C. Otero, ``A modular CPS architecture design based on ROS and docker,'' Int. J. Interact. Des. Manuf., vol. 11, no. 4, pp. 949 955, Nov. 2017.[17] X. Wan, X. Guan, T. Wang, G. Bai, and B.-Y. Choi, ``Application deployment using microservice and docker containers: Framework and optimization,'' J. Netw. Comput. Appl., vol. 119, pp. 97 109, Oct. 2018.[18] L. Abeni, A. Balsini, and T. Cucinotta, ``Container-based real-time scheduling in the linux kernel,'' ACM SIGBED Rev., vol. 16, no. 3, pp. 33 38, Nov. 2019.[19] T. Caraza-Harter and M. M. Swift, Blending Containers and Virtual Machines: A Study of Firecracker and Gvisor. New York, NY, USA: Association for Computing Machinery, 2020.[20] Z. Kozhirbayev and R. O. Sinnott, ``A performance comparison of container-based technologies for the cloud,'' Future Gener. Comput. Syst., vol. 68, pp. 175 182, Mar. 2017.[21] H. L. Ren and Y. P. Jiao, ``Study on the distributed real-time and embedded system middleware based on the DDS,'' Adv. Mater. Res., vols. 433 440, pp. 7522 7525, Feb. 2012.[22] B. Almadani and S. M. Mostafa, ``IIoT based multimodal communication model for agriculture and agro-industries,'' IEEE Access, vol. 9, pp. 10070 10088, 2021.[23] M. El Hariri, T. Youssef, M. Saleh, S. Faddel, H. Habib, and O. A. Mohammed, ``Aframework for analyzing and testing cyber physical interactions for smart grid applications,'' Electronics, vol. 8, no. 12, p. 1455, Dec. 2019.[24] I. Ungurean, N. C. Gaitan, and V. G. Gaitan, ``A middleware based architecture for the industrial Internet of Things,'' KSII Trans. Internet Inf. Syst., vol. 10, no. 7, pp. 2874 2891, 2016.[25] T. Coito, M. S. E. Martins, J. L. Viegas, B. Firme, J. Figueiredo, S. M. Vieira, and J. M. C. Sousa, ``A middleware platform for intelligent automation: An industrial prototype implementation,'' Comput. Ind., vol. 123, Dec. 2020, Art. no. 103329.[26] R. Beregi, G. Pedone, and I. Mezgár, ``A novel uid architecture for cyberphysical production systems,'' Int. J. Comput. Integr. Manuf., vol. 32, nos. 4 5, pp. 340 351, May 2019.[27] G. Chen, P. Wang, B. Feng, Y. Li, and D. Liu, ``The framework design of smart factory in discrete manufacturing industry based on cyber-physical system,'' Int. J. Comput. Integr. Manuf., vol. 33, no. 1, pp. 79 101, Jan. 2020.[28] M. Merdan, T. Hoebert, E. List, and W. Lepuschitz, ``Knowledge-based cyber-physical systems for assembly automation,'' Prod. Manuf. Res., vol. 7, no. 1, pp. 223 254, Jan. 2019.[29] A. González-Potes, W. A. Mata-López, V. Ibarra-Junquera, A. M. Ochoa-Brust, D. Martínez-Castro, and A. Crespo, ``Distributed multi-agent architecture for real-time wireless control networks of multiple plants,'' Eng. Appl. Artif. Intell., vol. 56, pp. 142 156, Nov. 2016.[30] G. M. Kurtzer, V. Sochat, and M. W. Bauer, ``Singularity: Scienti c containers for mobility of compute,'' PLoS ONE, vol. 12, no. 5, May 2017, Art. no. e0177459.Comunidad generalPublication16469e35-6f18-4e0c-acfe-e8a2e314fedfvirtual::2998-116469e35-6f18-4e0c-acfe-e8a2e314fedfvirtual::2998-1https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000195928virtual::2998-1LICENSElicense.txtlicense.txttext/plain; charset=utf-81665https://red.uao.edu.co/bitstreams/326bbecd-cb23-4f3f-99f5-502a438f6a36/download20b5ba22b1117f71589c7318baa2c560MD52ORIGINALComponent-based microservices for flexible and scalable automation of industrial bioprocesses.pdfComponent-based microservices for flexible and scalable automation of industrial bioprocesses.pdfTexto archivo completo del artículo de revista, PDFapplication/pdf5307070https://red.uao.edu.co/bitstreams/063135b7-610b-4afa-920e-91898ec4c287/downloadc9235980bc29f03d9c83856e6cec11a7MD53TEXTComponent-based microservices for flexible and scalable automation of industrial bioprocesses.pdf.txtComponent-based microservices for flexible and scalable automation of industrial bioprocesses.pdf.txtExtracted texttext/plain66012https://red.uao.edu.co/bitstreams/451e71a7-0559-4e77-9b41-19551cc84abf/downloadb7442cd7395df37ebcb93c120f6236ebMD54THUMBNAILComponent-based microservices for flexible and scalable automation of industrial bioprocesses.pdf.jpgComponent-based microservices for flexible and scalable automation of industrial bioprocesses.pdf.jpgGenerated Thumbnailimage/jpeg17019https://red.uao.edu.co/bitstreams/21cbfd40-794d-4f10-bcca-0ad8bee366db/download007045034a5503ecb96853df0f99604aMD5510614/13891oai:red.uao.edu.co:10614/138912024-03-07 16:47:43.801https://creativecommons.org/licenses/by-nc-nd/4.0/Derechos Reservados IEEE Access, 2021open.accesshttps://red.uao.edu.coRepositorio Digital Universidad Autonoma de Occidenterepositorio@uao.edu.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 |