Ricerc@Sapienza

The technological innovation and the relentless marketing of new electronic products with improved performance generate increasing quantities of Waste from Electrical and Electronic Equipment (WEEE). In this scenario, End-Of-Life (EOL) flat monitors and screens represent a category generating, as a consequence of the rapid change in technology, an important amount of waste. Considering future estimations, the implementation of an adequate recycling infrastructure is necessary. An efficient, reliable and low-cost analytical tool is thus needed to perform detection/control actions in order to assess: i) waste composition and ii) physical-chemical attributes of the resulting materials. The knowledge of these information is a requirement to set-up and to implement correct recycling actions. In this study, a cascade identification approach, based on Near InfraRed (NIR) - HyperSpectral Imaging (HSI), was carried out. More in detail, a four-steps classification was designed, implemented and set-up in order to recognize different materials occurring in a specific WEEE stream: EOL milled monitors and flat screens. Adopting the proposed approach, different material categories are correctly recognized and classified. Obtained results can be useful not only to set-up a quality control system, but also to improve sorting actions in this specific recycling sector.