Análisis del uso de Machine Learning como herramienta de optimización en sistemas PLC para procesos industriales inteligentes

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dc.contributor.advisorBecerra Angarita, Oscar Fernando
dc.contributor.authorHerrera Díaz, Andrés Reinaldo
dc.date.accessioned2026-10-02T17:47:57Z
dc.date.available2026-10-02T17:47:57Z
dc.date.issued2026-09-28
dc.descriptionEl presente trabajo desarrolla una revisión sistemática de la literatura orientada al análisis del uso de Machine Learning (ML) como herramienta de optimización en sistemas de Controladores Lógicos Programables (PLC) aplicados a procesos industriales inteligentes dentro del contexto de la Industria 4.0. Para ello, se realiza una evaluación crítica de la literatura científica con el fin de identificar las principales aplicaciones, beneficios, limitaciones, desafíos y tendencias de investigación asociadas a la integración de técnicas de aprendizaje automático en arquitecturas de automatización industrial basadas en PLC. Los resultados evidencian que el Machine Learning fortalece las capacidades de los sistemas PLC mediante aplicaciones en la optimización de procesos, el monitoreo inteligente, el mantenimiento predictivo y la detección de fallas, favoreciendo una mayor eficiencia operativa y una mejor toma de decisiones.
dc.description.abstractThis paper presents a systematic literature review focused on the use of Machine Learning (ML) as an optimization tool in Programmable Logic Controller (PLC) systems applied to intelligent industrial processes within the context of Industry 4.0. To this end, a critical evaluation of scientific literature is conducted to identify the main applications, benefits, limitations, challenges, and research trends associated with integrating machine learning techniques into PLC-based industrial automation architecture. The results demonstrate that Machine Learning strengthens the capabilities of PLC systems through applications in process optimization, intelligent monitoring, predictive maintenance, and fault detection, leading to greater operational efficiency and improved decision-making.
dc.description.degreelevelPregradospa
dc.description.degreenameIngeniero en Mecatrónicaspa
dc.description.domainhttps://www.ustabuca.edu.co/
dc.format.mimetypeapplication/pdf
dc.identifier.citationHerrera Díaz, A. R. (2026) Análisis del uso de Machine Learning como herramienta de optimización en sistemas PLC para procesos industriales inteligentes [Trabajo de grado]. Universidad Santo Tomás, Bucaramanga, Colombia.
dc.identifier.instnameinstname:Universidad Santo Tomásspa
dc.identifier.reponamereponame:Repositorio Institucional Universidad Santo Tomásspa
dc.identifier.repourlrepourl:https://repository.usta.edu.cospa
dc.identifier.urihttp://hdl.handle.net/11634/74444
dc.language.isospa
dc.publisherUniversidad Santo Tomásspa
dc.publisher.branchCRAI-USTA Bucaramanga
dc.publisher.facultyFacultad de Ingeniería Mecatrónicaspa
dc.publisher.programPregrado Ingeniería Mecatrónicaspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.localAbierto (Texto Completo)spa
dc.subject.keywordProgrammable Logic Controllers, analysis, benefits
dc.subject.lembInnovaciones Tecnológicas
dc.subject.lembAutomatización
dc.subject.proposalControladores Lógicos Programables, análisis, beneficios
dc.titleAnálisis del uso de Machine Learning como herramienta de optimización en sistemas PLC para procesos industriales inteligentes
dc.typebachelor thesis
dc.type.categoryFormación de Recurso Humano para la Ctel: Trabajo de grado de Pregrado
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.driveinfo:eu-repo/semantics/bachelorThesis
dc.type.localTrabajo de gradospa
dc.type.versioninfo:eu-repo/semantics/acceptedVersion

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