Prototipo de sistema de gestión de mantenimiento con análisis predictivo para optimizar recursos y eficiencia operativa para máquinas cerradoras de latas en una empresa de Guayaquil.

Abstract

This work aims to develop a prototype maintenance management system that incorporates predictive analytics techniques to support decision-making in the maintenance of can-sealing machines. The research begins with an analysis of the operational processes and types of maintenance applied in the industrial environment, identifying the need to structure technical information and reduce reliance on reactive maintenance. A client-server architecture with a relational database was designed, integrating modules for equipment management, work orders, spare parts inventory, preventive planning, and basic predictive analytics. The system calculates indicators such as Mean Time Between Failures (MTBF), days since the last failure, and estimated risk percentage, allowing equipment to be classified according to its criticality level. The prototype was validated through functional testing and evaluation by the company's technical experts, demonstrating its correct operation and usefulness as a support tool for improving planning and operational reliability. The proposal contributes to the transition toward a maintenance model based on data and technical indicators.