Estudo do processo de implementação da indústria 4.0 na manutenção de motores elétricos: planejamento e controle de manutenção preditiva e preventiva

Abstract

The aim of this study is to highlight the techniques and tools that have emerged from developments in the area, driven by the implementation of Industry 4.0. These approaches consist of integrating technology, collecting and analyzing data from equipment and sensors. Although there are manual alternatives, current practices incorporate technologies such as the Internet of Things (IoT) and Big Data, enabling substantial advances in data collection and analysis. This results in the creation of a detailed history of the equipment, enabling a direct comparison with its present state. Based on the data obtained, it is possible to identify the ideal time for intervention, enabling the development of more precise and highly reliable predictive and preventive maintenance planning and control. Applying these techniques not only optimizes operational efficiency, but also extends the useful life of industrial equipment. More effective management of maintenance processes results in resource savings, minimization of unexpected failures and increased productivity. In addition, continuous data analysis enables proactive adaptation to operating conditions, creating a more dynamic and resilient approach to industrial maintenance management in the context of Industry 4.0.