Desenvolvimento de uma plataforma para o gerenciamento de anomalias em usinas

Abstract

This work presents the development of a maintenance management portal focused on automating the registration, scheduling, and analysis of corrective and preventive maintenance. The system was developed using Python with Flask, along with HTML, CSS, JavaScript, and MariaDB for data storage. Key features include anomaly reporting, creating preventive maintenance plans, scheduling maintenance, and data visualization through dashboards. The implementation of the system automated processes previously performed manually, such as sending preventive maintenance alerts and scheduling interventions. Usability and integration tests were conducted to validate the portal's functionality, and the results indicated a significant improvement in operational efficiency and asset management. Additionally, the system proved to be an effective tool for maintenance data analysis, providing reports and indicators that support decision-making. Finally, the system contributed to reducing operational costs and increasing asset availability, highlighting the importance of digitization in maintenance management.