Automated System for OEE Management in the Industrial Sector

In today’s fast-paced manufacturing environment, the need to monitor production processes is becoming increasingly urgent. As companies strive to remain competitive in the Industry 4.0 era, they seek innovative solutions to enhance efficiency. This project addresses that need by providing a solution...

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Autores:
Gomez, Diego
Pantoja, Sofia
Acosta, Enoc
Arrieta, David
Gutiérrez, Sebastián
Tipo de recurso:
Article of journal
Fecha de publicación:
2025
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/14167
Acceso en línea:
https://hdl.handle.net/20.500.12585/14167
https://doi.org/10.32397/tesea.vol6.n1.810
Palabra clave:
Overall Equipment Effectiveness (OEE)
Industrial Automation
Smart Manufacturing
Real-Time Data Visualization
Production Optimization
Snap7 Communication Technology
IoT in Manufacturing
Industrial Iot
Rights
openAccess
License
Diego Gomez; Sofia Pantoja; Enoc Acosta, David Arrieta, Sebastián Gutiérrez - 2025
id UTB2_d9ccce3595c8d12115bd0b3b2c10c364
oai_identifier_str oai:repositorio.utb.edu.co:20.500.12585/14167
network_acronym_str UTB2
network_name_str Repositorio Institucional UTB
repository_id_str
dc.title.spa.fl_str_mv Automated System for OEE Management in the Industrial Sector
dc.title.translated.spa.fl_str_mv Automated System for OEE Management in the Industrial Sector
title Automated System for OEE Management in the Industrial Sector
spellingShingle Automated System for OEE Management in the Industrial Sector
Overall Equipment Effectiveness (OEE)
Industrial Automation
Smart Manufacturing
Real-Time Data Visualization
Production Optimization
Snap7 Communication Technology
IoT in Manufacturing
Industrial Iot
title_short Automated System for OEE Management in the Industrial Sector
title_full Automated System for OEE Management in the Industrial Sector
title_fullStr Automated System for OEE Management in the Industrial Sector
title_full_unstemmed Automated System for OEE Management in the Industrial Sector
title_sort Automated System for OEE Management in the Industrial Sector
dc.creator.fl_str_mv Gomez, Diego
Pantoja, Sofia
Acosta, Enoc
Arrieta, David
Gutiérrez, Sebastián
dc.contributor.author.eng.fl_str_mv Gomez, Diego
Pantoja, Sofia
Acosta, Enoc
Arrieta, David
Gutiérrez, Sebastián
dc.subject.eng.fl_str_mv Overall Equipment Effectiveness (OEE)
Industrial Automation
Smart Manufacturing
Real-Time Data Visualization
Production Optimization
Snap7 Communication Technology
IoT in Manufacturing
Industrial Iot
topic Overall Equipment Effectiveness (OEE)
Industrial Automation
Smart Manufacturing
Real-Time Data Visualization
Production Optimization
Snap7 Communication Technology
IoT in Manufacturing
Industrial Iot
description In today’s fast-paced manufacturing environment, the need to monitor production processes is becoming increasingly urgent. As companies strive to remain competitive in the Industry 4.0 era, they seek innovative solutions to enhance efficiency. This project addresses that need by providing a solution to capture OEE (Overall Equipment Effectiveness) measurements from machines in the drum-filling industry, specifically targeting semi-automatic equipment. The primary objective is to streamline decision-making and improve data management performance. In collaboration with Alianza Team S.A., this article outlines the detailed design and development process of a web platform called AutOEE, which integrates the Snap7 communication technology. Additionally, the article presents technical experiments, including tests conducted using a PLC provided by ELEIA to simulate real production environments. These tests verified system stability, web interface responsiveness, and accurate data extraction, with reconnection features to recover from connectivity loss. The platform also supports real-time and historical OEE data visualization, with customizable views for specific days and shifts. User feedback, gathered through a web interface test with randomized data, was overwhelmingly positive (98%), praising ease of use, relevance, and load times. However, suggestions for improvement included simplifying access to historical data, adding PDF report generation, improving security, and enhancing error reporting. These insights will guide future platform updates.
publishDate 2025
dc.date.accessioned.none.fl_str_mv 2025-02-06 00:00:00
2025-08-16T14:15:16Z
dc.date.available.none.fl_str_mv 2025-02-06 00:00:00
dc.date.issued.none.fl_str_mv 2025-02-06
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.driver.eng.fl_str_mv info:eu-repo/semantics/article
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dc.type.local.eng.fl_str_mv Journal article
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dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/14167
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dc.identifier.doi.none.fl_str_mv 10.32397/tesea.vol6.n1.810
dc.identifier.eissn.none.fl_str_mv 2745-0120
url https://hdl.handle.net/20.500.12585/14167
https://doi.org/10.32397/tesea.vol6.n1.810
identifier_str_mv 10.32397/tesea.vol6.n1.810
2745-0120
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language eng
dc.relation.references.eng.fl_str_mv P. Muchiri and L. Pintelon. Performance measurement using overall equipment effectiveness (oee): literature review and practical application discussion. International Journal of Production Research, 46(13):3517–3535, 2008. [2] X. Zhu. Analysis and improvement of enterprise’s equipment effectiveness based on oee. In 2011 International Conference on Electronics, Communications and Control (ICECC), pages 4167–4171, Ningbo, China, 2011. [3] I. Zennaro, D. Battini, F. Sgarbossa, A. Persona, and R. De Marchi. Micro downtime: Data collection, analysis and impact on oee in bottling lines the san benedetto case study. International Journal of Quality & Reliability Management, 35(4):965–995, 2018. [4] Seiichi Nakajima. Introduction to TPM: Total Productive Maintenance. Productivity Press, 1988. [5] M. Swamidass. Encyclopedia of Production and Manufacturing Management. Springer, 2000. [6] D. Guillén, D. Gómez, I. Hernández, D. Charris, J. González, D. León, and M. Sanjuán. Integrated methodology for industrial facilities management and design based on fca and lean manufacturing principles. Facilities, 38(7/8):523–538, 2020. [7] P. Jonsson and M. Lesshammar. Evaluation and improvement of manufacturing performance measurement systems – the role of oee. International Journal of Operations & Production Management, 19(1):55–78, 1999. [8] H. Wang and P. J. Schniederjans. A multi-objective decision model for lean project selection. International Journal of Production Economics, 140(2):654–666, 2012. [9] L.d.C. Ng Corrales, M.P. Lambán, M.E. Hernandez Korner, and J. Royo. Overall equipment effectiveness: Systematic literature review and overview of different approaches. Applied Sciences, 10:6469, 2020. [10] L. Zemanová and P. Rudolf. Flow inside the sidewall gaps of hydraulic machines: A review. Energies, 13:6617, 2020. [11] M. Diakomihalis, G. Stavaraki, and P. Tachynakis. Financial accounting for not-for-profit organizations: Proposal for a specialized accounting system for the nfpos sector. 2019. [12] Luis Arismendy, Carlos Cárdenas, Diego Gómez, Aymer Maturana, Ricardo Mejía, and Christian G. Quintero M. Intelligent system for the predictive analysis of an industrial wastewater treatment process. Sustainability, 12(16), 2020. [13] Luis Arismendy, Carlos Cárdenas, Diego Gómez, Aymer Maturana, Ricardo Mejía, and Christian G. Quintero M. A prescriptive intelligent system for an industrial wastewater treatment process: Analyzing ph as a first approach. Sustainability, 13(8), 2021. [14] Lifeder. Automatización industrial. https://www.lifeder.com/automatizacion-industrial/, 2022. Último acceso: 5 de julio de 2022. [15] D. Nardella. Snap7, an open-source siemens s7 communication library. https://snap7.sourceforge.net/. [16] D. K. Drozd. Implicación del cliente en el desarrollo ágil. https://www.atlassian.com/es/agile/agile-conversations/customerresearch- tips. [17] Rockwell Automation. Factorytalk metrics. https://www.rockwellautomation.com/en-us/products/software/factorytalk/ operationsuite/metrics.html, 2025. Accessed: 2025-05-17. [18] Siemens AG. Simatic it: Manufacturing execution system (mes). https://plm.sw.siemens.com/en-US/opcenter/manufacturingexecution- system-mes-capabilities/, 2025. Accessed: 2025-05-17. [19] C. Viloria-Núñez, F. J. Vázquez, and C. M. Fernández-Márquez. A review of the digital transformation maturity models for smes in search of a self-assessment. In 2022 IEEE ANDESCON, pages 1–6. IEEE, 2022. [20] JanSquare. Openoee: Open source overall equipment effectiveness. https://github.com/JanSquare/OpenOEE, 2023. Accessed: 2025-05-17. [21] Spruik. Libre: Open source manufacturing execution and performance monitoring. https://github.com/Spruik/Libre, 2023. Accessed: 2025-05-17. [22] John Smith and Maria Lee. Best practices in collaborative industrial software development. Journal of Industrial Software Engineering, 15(4):200–215, 2023. [23] Martinekuan. Datos no relacionales y nosql - azure architecture center. https://learn.microsoft.com/es-es/azure/architecture/ data-guide/big-data/non-relational-data. [24] D. S. C. Enríquez and C. A. A. Chango. Estudio e implementación de un sistema de automatización para el incremento del oee en un pulpo serigráfico. http://dspace.espoch.edu.ec/bitstream/123456789/4937/1/108T0130.docx, 2016. [25] A. Hernández, N. Peña, and J. Cardona. Propuesta de mejora para la línea de laminado en la producción de empaques flexibles mediante el seguimiento del oee. http://repository.icesi.edu.co/biblioteca_digital/handle/10906/87598. [26] Y. H. Li, L. C. G. V. Inoue, and R. Sinha. Real-time oee visualisation for downtime detection. In 2022 IEEE 20th International Conference on Industrial Informatics (INDIN), pages 729–734, Perth, Australia, 2022. [27] J. Smith and A. Brown. Efficient plc communication using snap7 for industrial automation. IEEE Transactions on Industrial Informatics, 16(5):3400–3408, 2020. [28] L. Johnson and M. Davis. Asynchronous server architectures for real-time industrial systems. In Proceedings of the IEEE International Conference on Industrial Technology, pages 1223–1228, 2019. [29] Ley n.º 1273, ley 1273 de 2009. https://www.sic.gov.co/recursos_user/documentos/normatividad/Ley_1273_2009.pdf, 2009.
dc.relation.ispartofjournal.eng.fl_str_mv Transactions on Energy Systems and Engineering Applications
dc.relation.citationvolume.eng.fl_str_mv 6
dc.relation.citationstartpage.none.fl_str_mv 1
dc.relation.citationendpage.none.fl_str_mv 18
dc.relation.bitstream.none.fl_str_mv https://revistas.utb.edu.co/tesea/article/download/810/454
dc.relation.citationedition.eng.fl_str_mv Núm. 1 , Año 2025 : Transactions on Energy Systems and Engineering Applications
dc.relation.citationissue.eng.fl_str_mv 1
dc.rights.eng.fl_str_mv Diego Gomez; Sofia Pantoja; Enoc Acosta, David Arrieta, Sebastián Gutiérrez - 2025
dc.rights.uri.eng.fl_str_mv https://creativecommons.org/licenses/by/4.0
dc.rights.accessrights.eng.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.creativecommons.eng.fl_str_mv This work is licensed under a Creative Commons Attribution 4.0 International License.
dc.rights.coar.eng.fl_str_mv http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Diego Gomez; Sofia Pantoja; Enoc Acosta, David Arrieta, Sebastián Gutiérrez - 2025
https://creativecommons.org/licenses/by/4.0
This work is licensed under a Creative Commons Attribution 4.0 International License.
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.eng.fl_str_mv application/pdf
dc.publisher.eng.fl_str_mv Universidad Tecnológica de Bolívar
dc.source.eng.fl_str_mv https://revistas.utb.edu.co/tesea/article/view/810
institution Universidad Tecnológica de Bolívar
repository.name.fl_str_mv Repositorio Digital Universidad Tecnológica de Bolívar
repository.mail.fl_str_mv bdigital@metabiblioteca.com
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spelling Gomez, DiegoPantoja, SofiaAcosta, EnocArrieta, DavidGutiérrez, Sebastián2025-02-06 00:00:002025-08-16T14:15:16Z2025-02-06 00:00:002025-02-06https://hdl.handle.net/20.500.12585/14167https://doi.org/10.32397/tesea.vol6.n1.81010.32397/tesea.vol6.n1.8102745-0120In today’s fast-paced manufacturing environment, the need to monitor production processes is becoming increasingly urgent. As companies strive to remain competitive in the Industry 4.0 era, they seek innovative solutions to enhance efficiency. This project addresses that need by providing a solution to capture OEE (Overall Equipment Effectiveness) measurements from machines in the drum-filling industry, specifically targeting semi-automatic equipment. The primary objective is to streamline decision-making and improve data management performance. In collaboration with Alianza Team S.A., this article outlines the detailed design and development process of a web platform called AutOEE, which integrates the Snap7 communication technology. Additionally, the article presents technical experiments, including tests conducted using a PLC provided by ELEIA to simulate real production environments. These tests verified system stability, web interface responsiveness, and accurate data extraction, with reconnection features to recover from connectivity loss. The platform also supports real-time and historical OEE data visualization, with customizable views for specific days and shifts. User feedback, gathered through a web interface test with randomized data, was overwhelmingly positive (98%), praising ease of use, relevance, and load times. However, suggestions for improvement included simplifying access to historical data, adding PDF report generation, improving security, and enhancing error reporting. These insights will guide future platform updates.application/pdfengUniversidad Tecnológica de BolívarDiego Gomez; Sofia Pantoja; Enoc Acosta, David Arrieta, Sebastián Gutiérrez - 2025https://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessThis work is licensed under a Creative Commons Attribution 4.0 International License.http://purl.org/coar/access_right/c_abf2https://revistas.utb.edu.co/tesea/article/view/810Overall Equipment Effectiveness (OEE)Industrial AutomationSmart ManufacturingReal-Time Data VisualizationProduction OptimizationSnap7 Communication TechnologyIoT in ManufacturingIndustrial IotAutomated System for OEE Management in the Industrial SectorAutomated System for OEE Management in the Industrial SectorArtículo de revistainfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Journal articleTextinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85P. Muchiri and L. Pintelon. Performance measurement using overall equipment effectiveness (oee): literature review and practical application discussion. International Journal of Production Research, 46(13):3517–3535, 2008. [2] X. Zhu. Analysis and improvement of enterprise’s equipment effectiveness based on oee. In 2011 International Conference on Electronics, Communications and Control (ICECC), pages 4167–4171, Ningbo, China, 2011. [3] I. Zennaro, D. Battini, F. Sgarbossa, A. Persona, and R. De Marchi. Micro downtime: Data collection, analysis and impact on oee in bottling lines the san benedetto case study. International Journal of Quality & Reliability Management, 35(4):965–995, 2018. [4] Seiichi Nakajima. Introduction to TPM: Total Productive Maintenance. Productivity Press, 1988. [5] M. Swamidass. Encyclopedia of Production and Manufacturing Management. Springer, 2000. [6] D. Guillén, D. Gómez, I. Hernández, D. Charris, J. González, D. León, and M. Sanjuán. Integrated methodology for industrial facilities management and design based on fca and lean manufacturing principles. Facilities, 38(7/8):523–538, 2020. [7] P. Jonsson and M. Lesshammar. Evaluation and improvement of manufacturing performance measurement systems – the role of oee. International Journal of Operations & Production Management, 19(1):55–78, 1999. [8] H. Wang and P. J. Schniederjans. A multi-objective decision model for lean project selection. International Journal of Production Economics, 140(2):654–666, 2012. [9] L.d.C. Ng Corrales, M.P. Lambán, M.E. Hernandez Korner, and J. Royo. Overall equipment effectiveness: Systematic literature review and overview of different approaches. Applied Sciences, 10:6469, 2020. [10] L. Zemanová and P. Rudolf. Flow inside the sidewall gaps of hydraulic machines: A review. Energies, 13:6617, 2020. [11] M. Diakomihalis, G. Stavaraki, and P. Tachynakis. Financial accounting for not-for-profit organizations: Proposal for a specialized accounting system for the nfpos sector. 2019. [12] Luis Arismendy, Carlos Cárdenas, Diego Gómez, Aymer Maturana, Ricardo Mejía, and Christian G. Quintero M. Intelligent system for the predictive analysis of an industrial wastewater treatment process. Sustainability, 12(16), 2020. [13] Luis Arismendy, Carlos Cárdenas, Diego Gómez, Aymer Maturana, Ricardo Mejía, and Christian G. Quintero M. A prescriptive intelligent system for an industrial wastewater treatment process: Analyzing ph as a first approach. Sustainability, 13(8), 2021. [14] Lifeder. Automatización industrial. https://www.lifeder.com/automatizacion-industrial/, 2022. Último acceso: 5 de julio de 2022. [15] D. Nardella. Snap7, an open-source siemens s7 communication library. https://snap7.sourceforge.net/. [16] D. K. Drozd. Implicación del cliente en el desarrollo ágil. https://www.atlassian.com/es/agile/agile-conversations/customerresearch- tips. [17] Rockwell Automation. Factorytalk metrics. https://www.rockwellautomation.com/en-us/products/software/factorytalk/ operationsuite/metrics.html, 2025. Accessed: 2025-05-17. [18] Siemens AG. Simatic it: Manufacturing execution system (mes). https://plm.sw.siemens.com/en-US/opcenter/manufacturingexecution- system-mes-capabilities/, 2025. Accessed: 2025-05-17. [19] C. Viloria-Núñez, F. J. Vázquez, and C. M. Fernández-Márquez. A review of the digital transformation maturity models for smes in search of a self-assessment. In 2022 IEEE ANDESCON, pages 1–6. IEEE, 2022. [20] JanSquare. Openoee: Open source overall equipment effectiveness. https://github.com/JanSquare/OpenOEE, 2023. Accessed: 2025-05-17. [21] Spruik. Libre: Open source manufacturing execution and performance monitoring. https://github.com/Spruik/Libre, 2023. Accessed: 2025-05-17. [22] John Smith and Maria Lee. Best practices in collaborative industrial software development. Journal of Industrial Software Engineering, 15(4):200–215, 2023. [23] Martinekuan. Datos no relacionales y nosql - azure architecture center. https://learn.microsoft.com/es-es/azure/architecture/ data-guide/big-data/non-relational-data. [24] D. S. C. Enríquez and C. A. A. Chango. Estudio e implementación de un sistema de automatización para el incremento del oee en un pulpo serigráfico. http://dspace.espoch.edu.ec/bitstream/123456789/4937/1/108T0130.docx, 2016. [25] A. Hernández, N. Peña, and J. Cardona. Propuesta de mejora para la línea de laminado en la producción de empaques flexibles mediante el seguimiento del oee. http://repository.icesi.edu.co/biblioteca_digital/handle/10906/87598. [26] Y. H. Li, L. C. G. V. Inoue, and R. Sinha. Real-time oee visualisation for downtime detection. In 2022 IEEE 20th International Conference on Industrial Informatics (INDIN), pages 729–734, Perth, Australia, 2022. [27] J. Smith and A. Brown. Efficient plc communication using snap7 for industrial automation. IEEE Transactions on Industrial Informatics, 16(5):3400–3408, 2020. [28] L. Johnson and M. Davis. Asynchronous server architectures for real-time industrial systems. In Proceedings of the IEEE International Conference on Industrial Technology, pages 1223–1228, 2019. [29] Ley n.º 1273, ley 1273 de 2009. https://www.sic.gov.co/recursos_user/documentos/normatividad/Ley_1273_2009.pdf, 2009.Transactions on Energy Systems and Engineering Applications6118https://revistas.utb.edu.co/tesea/article/download/810/454Núm. 1 , Año 2025 : Transactions on Energy Systems and Engineering Applications120.500.12585/14167oai:repositorio.utb.edu.co:20.500.12585/141672025-08-16 09:15:16.358https://creativecommons.org/licenses/by/4.0Diego Gomez; Sofia Pantoja; Enoc Acosta, David Arrieta, Sebastián Gutiérrez - 2025metadata.onlyhttps://repositorio.utb.edu.coRepositorio Digital Universidad Tecnológica de Bolívarbdigital@metabiblioteca.com

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