Aplicação da Engenharia Virtual como Alternativa para análise Estrutural no Setor automobilístico: um estudo de caso

Abstract

In order to increase productivity and reduce costs, best maintenance practices must be applied in companies to ensure asset availability. To control the condition of equipment, maintenance must use predictive practices, identifying the ideal time for intervention on a machine. In this scenario, Industry 4.0 appears as an innovative proposal, incorporating technologies that integrate sensors into equipment, allowing real-time monitoring of variables such as vibration and temperature. In order to increase the availability of rotating equipment in a recycled paper industry, this work proposes to analyze the implementation of an online predictive maintenance strategy. In the study, fundamental maintenance concepts were explored, highlighting the main predictive techniques and highlighting the benefits and methods for the effective application of real-time monitoring. The results obtained after the first year of implementation were significant, showing a reduction in breakdowns, improvements in maintenance costs and optimization of predictive maintenance processes. The effectiveness of the proposed methodology stands out, with a 78% decrease in the unavailability of monitored assets. These positive results emphasize the favorable impact on the operational efficiency of the recycled paper industry, reinforcing the importance of the predictive approach in asset management and strengthening the integration of Industry 4.0 technologies.