Propuesta de implementación de Inteligencia Artificial para mejorar la confiabilidad de los equipos rotativos en el sector industrial en Cartagena, Colombia
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Fecha
2025
Autores
Hernández Reyes, Francisco Javier
Valdivieso Padilla, Omar de Jesús
Lizcano Ortiz, Carlos Fernando
Toncel Rosado, Javier Andrés
Barrios Plata, José Miguel
Velásquez Suárez, Karina
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Ediciones Universidad Simón Bolívar
Facultad de Ingenierías
Facultad de Ingenierías
Resumen
La operación de equipos rotativos es clave para la eficiencia y reducción de
costos, lo que resalta la necesidad de aplicar nuevas técnicas de mantenimiento frente a los métodos
tradicionales, que presentan altos índices de fallas. Objetivo: Formular una propuesta de solución
basada en Inteligencia Artificial (IA) para mejorar la confiabilidad de los equipos rotativos en el
sector industrial de Cartagena considerando su viabilidad técnica, económica y organizacional.
Materiales y métodos: Se realizó un estudio descriptivo de enfoque mixto para conocer la
eficiencia de las técnicas de mantenimiento convencionales y la percepción sobre la
implementación de IA para mejorar la confiabilidad de los equipos. Resultados: Se utilizó una
muestra de 17 expertos en el área de mantenimiento de equipos rotativos. Se estudiaron dos
variables: 1. Solución basada en inteligencia artificial. 2. Confiabilidad de los equipos rotativos en
un entorno industrial. Se realizó el análisis según los objetivos específicos, se obtuvo que el 42,9%
de los expertos están totalmente de acuerdo con que las maquinarias presentan fallas frecuentes y
solo el 0.9% está en desacuerdo, además, el 57,7% estaba de acuerdo con que la utilización de IA
mejoraría los procesos operativos, asimismo, el 1,2% no estaba de acuerdo, lo cual respalda que
la utilización de IA supone una mejora para el mantenimiento. Conclusiones: Este estudio
proporciona la percepción de expertos en el área industrial sobre la utilización IA para el
mantenimiento de los equipos, demostrando que podría ser un factor diferencial en la confiabilidad
y la eficiencia operativa.
The operation of rotating equipment is key to achieving efficiency and reducing costs, highlighting the need to implement new maintenance techniques over traditional methods, which show high failure rates. Objective: To formulate a solution proposal based on Artificial Intelligence (AI) to improve the reliability of rotating equipment in the industrial sector in Cartagena, considering its technical, economic, and organizational feasibility. Materials and Methods: A descriptive study with a mixed-methods approach was conducted to evaluate the efficiency of conventional maintenance techniques and the perception of AI implementation to enhance equipment reliability. Results: A sample of 17 experts in rotating equipment maintenance was used. Two variables were studied: (1) AI-based solution, and (2) Reliability of rotating equipment in an industrial setting. The analysis was carried out according to the specific objectives. Results showed that 42.9% of the experts strongly agreed that machinery frequently experiences failures, while only 0.9% disagreed. Additionally, 57.7% agreed that AI implementation would improve operational processes, while only 1.2% disagreed. These findings support the notion that AI represents an improvement for maintenance strategies. Conclusions: This study provides insight into the perception of industry experts regarding the use of AI in equipment maintenance, demonstrating its potential as a differentiating factor in improving reliability and operational efficiency.
The operation of rotating equipment is key to achieving efficiency and reducing costs, highlighting the need to implement new maintenance techniques over traditional methods, which show high failure rates. Objective: To formulate a solution proposal based on Artificial Intelligence (AI) to improve the reliability of rotating equipment in the industrial sector in Cartagena, considering its technical, economic, and organizational feasibility. Materials and Methods: A descriptive study with a mixed-methods approach was conducted to evaluate the efficiency of conventional maintenance techniques and the perception of AI implementation to enhance equipment reliability. Results: A sample of 17 experts in rotating equipment maintenance was used. Two variables were studied: (1) AI-based solution, and (2) Reliability of rotating equipment in an industrial setting. The analysis was carried out according to the specific objectives. Results showed that 42.9% of the experts strongly agreed that machinery frequently experiences failures, while only 0.9% disagreed. Additionally, 57.7% agreed that AI implementation would improve operational processes, while only 1.2% disagreed. These findings support the notion that AI represents an improvement for maintenance strategies. Conclusions: This study provides insight into the perception of industry experts regarding the use of AI in equipment maintenance, demonstrating its potential as a differentiating factor in improving reliability and operational efficiency.
Descripción
Palabras clave
Inteligencia artificial, Equipos rotativos, Mantenimiento predictivo, Confiabilidad
