Integración de inteligencia artificial y mantenimiento predictivo como estrategia de prevención en seguridad y salud ocupacional en entornos industriales

Carlos Chen; Alexis Chen; Miguel Pandales; José Luis Georget; Michael Castillo; Alex Blandford

doi:10.70625/rmis/630

Autores/as

Carlos Chen Universidad de Panamá Autor/a
Alexis Chen Universidad de Panamá Autor/a https://orcid.org/0009-0008-8297-5552
Miguel Pandales Universidad de Panamá Autor/a
José Luis Georget Universidad de Panamá Autor/a https://orcid.org/0009-0000-1232-2814
Michael Castillo Universidad de Panamá Autor/a https://orcid.org/0009-0007-0466-863X
Alex Blandford Universidad de Panamá Autor/a https://orcid.org/0009-0000-4836-8814

DOI:

https://doi.org/10.70625/rmis/630

Palabras clave:

Inteligencia artificial, Mantenimiento predictivo, Seguridad y salud ocupacional, Industria 4.0, Gestión del riesgo

Resumen

La transformación digital industrial ha impulsado la adopción de modelos de inteligencia artificial aplicados al mantenimiento predictivo, orientados principalmente a la optimización operativa. No obstante, su integración explícita con sistemas de seguridad y salud ocupacional (SSO) continúa siendo limitada. El presente estudio analiza la evidencia científica sobre la articulación entre inteligencia artificial, mantenimiento predictivo y prevención de riesgos laborales en entornos industriales. Se desarrolló una revisión sistemática siguiendo el protocolo PRISMA 2020 (Page et al., 2021) en bases de datos indexadas entre 2014 y 2025, seleccionándose 65 estudios para análisis comparativo. Los resultados evidencian que el 52% de las investigaciones priorizan métricas de eficiencia técnica sin evaluar impactos en seguridad laboral, mientras que solo el 5% integra indicadores explícitos de reducción de riesgos. Se propone el Modelo Integrado Predictivo para Seguridad y Salud Ocupacional (MIP-SSO) y el Índice Predictivo de Riesgo Ocupacional como marco conceptual para vincular probabilidad de falla técnica y nivel de exposición humana. Se concluye que la integración sistémica entre mantenimiento predictivo basado en IA y gobernanza preventiva constituye una oportunidad estratégica para fortalecer la seguridad industrial en economías emergentes.

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