Análise de vibração em máquinas industriais com inteligência artificial para previsão de falhas e classificação de defeitos

Abstract

This article presents an integrated software and hardware system for analyzing vibrations in industrial machines. The main objective is to minimize unplanned stops and maximize OEE (Overall Equipment Effectiveness), a crucial indicator for industrial productivity. The system uses vibration sensors, artificial intelligence techniques with supervised learning and a dataset to classify possible defects. Based on the classification, the system can generate alerts and recommendations for corrective actions to avoid failures and unplanned stops. This contributes to reducing maintenance costs, increasing productivity, industrial safety and maximizing OEE.