Bibliometric analysis of studies involving e-waste: a critical review.

The correct destination of waste is an essential factor for sustainable development. Electronic waste, which is very toxic, is the type of waste with the highest rate of increase in its generation. For these reasons, the amount of research on this topic increases year by year, as shown by the literature review carried out by this study. This review aims to identify the main characteristics and proposals of the main study on electronic waste and verify how Brazil is inserted globally in the research on e-waste. Another objective is to suggest a path for researchers who want to start research on e-waste by identifying the keywords most used in the analyzed articles. The results evidenced that the most published countries on the subject are China, the USA, and India. Brazil is in a position of little prominence concerning its research production on the subject. Most of the central studies we analyzed use case study and literature review as the research method. Among the 44 articles analyzed, only one proposed a destination for e-waste. It highlights the need for more research focusing on the environmentally correct destination of e-waste. A good way to start a search on electronic waste is to use the keywords identified in this study, especially those used most frequently in the analyzed articles.

Vibrations in CDFW.

Continuous drive friction welding is a solid-state welding process that has been experimentally proven to be a fast and reliable method. This is a complex process; deformations in the viscosity of a material alter the friction between the surfaces of the pieces. All these dynamics cause changes in the vibration signals; the interpretation of these signals can reveal important information. The vibration signals generated during the friction and forging stages are measured on the stationary part of the structure to determine the influence of the manipulated variables on the time domain statistical characteristics (root mean square, peak value, crest factor, and kurtosis). In the frequency domain, empirical mode decomposition is used to characterize frequencies. It was observed that it is possible to identify the effects of the manipulated variables on the calculated statistical characteristics. The results also indicate that the effect of manipulated variables is stronger on low-frequency signals.