Aplicación De Inteligencia Artificial Y Analítica Predictiva Para Optimizar La Gestión De Mantenimiento De Maquinaria Amarilla Pesada En El Departamento Del Huila

Abstract

In the Huila Department, there's a large fleet of heavy machinery that includes backhoes, motor graders, loaders, bulldozers, and dump trucks, which are essential for road infrastructure and public works. However, there has been a noticeable decline in the performance and availability of this machinery, which shows repeated breakdowns, long downtime, and rising repair costs, causing delays in projects and financial losses. This problem is worsened by a lack of technical and logistical management, as well as maintenance policies and a lack of a predictive maintenance culture.

In response to this situation, the project 'Implement an Artificial Intelligence and Predictive Analytics Model to Optimize Maintenance Management of Heavy Machinery in Huila' was developed, using the analysis of historical data, oil analysis, vibrations, and maintenance records, with the aim of estimating equipment lifespan and improving operational decision-making. The proposed procedure is based on the ISO14224 technical standard, which implements monitoring of critical variables (vibration, temperature, lubrication) allowing the government entity to anticipate failures and extend the life of the equipment.