Monitoramento do desgaste de ferramentas de usinagem de painéis sanduíche por meio de análise de vibrações e microscopia

Abstract

The application of composite materials has expanded across various areas of modern industry, driven by the search for lighter and stronger components. These materials exhibit characteristics such as high specific stiffness, corrosion resistance, and low mass, making them attractive to sectors such as automotive, naval, sports, wind energy, and biomedical segments. However, it is in the aeronautical industry that composite materials have the most significant use, being employed in the manufacture of fuselages, wings, and internal components, with the main purpose of reducing the total weight of aircraft, promoting greater fuel efficiency, increased flight range, and reduced emissions. The processing of these materials is largely carried out by CNC machining centers, equipped with cutting tools developed to handle the abrasiveness and heterogeneity of composites. Such tools have high development and acquisition costs and are subject to accelerated wear during the process, which reinforces the need for strategies that allow for maximum utilization of their service life without compromising the quality and integrity of the final product. In this context, this study proposes monitoring the condition of cutting tools through a combination of direct and indirect methods. The direct method employs geometric characterization of the cutting edges of the tools using microscopy, while the indirect method utilizes the analysis of mechanical vibrations captured by sensors integrated into the CNC machine spindle. The methodology consists of the periodic collection of vibration signals throughout the tool lifespan, followed by analysis of the cutting edge condition through microscopic image analysis. The correlation between vibration levels and wear conditions observed in the microscopy analyses highlights the potential for using this information together to build a predictive model for estimating the optimal tool usage time, contributing to greater production efficiency.