Proposta de uma metodologia de análise estatística de um banco de dados de manufatura aditiva para determinação dos parâmetros de impressão 3D na resistência à tração

Abstract

The fourth industrial revolution, also called industry 4.0, is a modern concept that has revolutionized the way of communication between all components of a production process. This revolution is based on several technologies, looking for innovation with the generation of new business models and optimization of production processes, always centered on competitiveness and agility. In this context, Big Data and Analytics stands out for allowing the generation of information with the potential to support decision-making at different levels of companies. Another relevant technology is Additive Manufacturing, capable of manufacturing parts with the addition of material, having different processes, materials and printing parameters, capable of changing beneficially or not the mechanical resistance of the produced parts. The present research aims to propose a statistical analysis methodology, in a 3D printing database, to determine the influence of printing parameters on the maximum tensile strength in a part manufactured with fusion and deposition modeling, a 3D printing technology. The analysis chosen was the Multiple Linear Regression, evaluating the parameters of layer height, wall thickness, infill density, infill pattern, nozzle temperature, table temperature and printing speed, being that only the first three were identified as significant and with a result of the coefficient of determination of 78.05%. For the empirical evaluation of the regression equations found, tensile strength tests were performed with 18 specimens, made of ABS and PLA, designed according to ASTM D 638-02a and printed in 3D. The tests were performed by a universal testing machine EMIC DL-200 and their results confirmed those indicators of the statistical procedure.