https://repositorio.ifpe.edu.br/xmlui/handle/123456789/470 Trabalho de Conclusão de Curso - TCC 2026-04-20T10:54:24Z https://repositorio.ifpe.edu.br/xmlui/handle/123456789/1835 Análise de OEE para melhoria da eficiência de uma máquina de sopro In the current scenario, where companies are increasingly seeking solutions aimed at improving and perfecting processes, there is a significant rise in the use of indicators to promote better operational efficiency. This study aims to analyze the OEE (Overall Equipment Efficiency) index in a blow molding machine, a parameter widely used in the maintenance field. A well-monitored and managed OEE can result in greater equipment efficiency and a reduction in costs related to breakdowns and downtime. The research is qualitative-quantitative and explanatory in nature; data from the machine itself will be analyzed through a supervisory system over a period of four months, collecting operational and inactivity data from a plastic segment machine, monitoring shifts and random days. Through the analysis of OEE, the goal is to identify the machine's main needs and improve the indicator’s efficiency, enabling improvements in its performance and maintenance management. 2025-07-23T00:00:00Z https://repositorio.ifpe.edu.br/xmlui/handle/123456789/1612 Utilização das previsões da temperatura ambiente como entrada para a estimativa de radiação solar Due to the great need to use solar radiation for renewable energy generation and the fact that many locations do not have radiation meters, this study emerged as a research project to verify whether it is possible to calculate radiation values using correlation models between radiation and temperature, based on temperature forecast data. Data from one year and one month of forecasts were tested for two locations on the northeastern coast, and the four best correlation models that obtained good results in coastal regions were selected for calculating radiation values. The performance of the models was evaluated using two performance coefficients: the coefficient of determination (R²) and the root mean square error (RMSE). It was observed that the four models obtained similar results, with the Li et al. (LI) which presented the best results in the evaluations with R² values approximately 0.67 in the measured values and 0.33 in the predicted values, and the RMSE obtaining values close to 2.8 MJ.m-²d-¹in the measured values and 4.1 MJ. m-²d-¹ in the predicted values. 2025-03-20T00:00:00Z