Desenvolvimento de uma bancada para análise corretiva de equipamentos de sucção em indústria de grande porte - aplicação na confiabilidade e melhoria contínua dos processos de manutenção

Abstract

Vibration analysis as a predictive technique offers several advantages in determining the condition of industrial equipment. Within the concept of Industry 4.0, vibration sensors enable real-time equipment monitoring, thereby ensuring an operational history of the asset and helping to prevent the failure of machines or specific mechanical components, such as industrial fans. Fans are crucial mechanical assembly devices responsible for maintaining stable temperatures, ensuring adequate airflow, and managing the thermal conditions of delicate components in various industries. However, the performance and reliability of industrial fans can be affected by multiple factors, including vibrations, maintenance issues, and operational challenges. The criteria set by ISO 10816 provide significant support in characterizing the current state of the machine and are widely used for decision-making regarding the replacement of components. In the present study, using the predictive maintenance technique of vibration analysis by NBR 10082, a self-aligning ball bearing was evaluated, comparing its vibration conditions with the ISO 10816 vibration standard. Following the replacement of the faulty fan, it was observed that reliability decreased from 85 % to 39 % over three months, and the failure prediction rate increased from 0.5 to 1.6.