  The waste of electrical and electronic equipment has been increased due to
the fast evolution of technology products and competition of many IT sectors.
Every year millions of tons of electronic waste are thrown into the environment
which causes high consequences for human health. Therefore, it is crucial to
control this waste flow using technology, especially using Artificial
Intelligence but also reclamation of critical raw materials for new production
processes. In this paper, we focused on the measurement of recyclability of
waste electronic components (WECs) from waste printed circuit boards (WPCBs)
using mathematical innovation model. This innovative approach evaluates both
the recyclability and recycling difficulties of WECs, integrating an AI model
for improved disassembly and sorting. Assessing the recyclability of individual
electronic components present on WPCBs provides insight into the recovery
potential of valuable materials and indicates the level of complexity involved
in recycling in terms of economic worth and production utility. This novel
measurement approach helps AI models in accurately determining the number of
classes to be identified and sorted during the automated disassembly of
discarded PCBs. It also facilitates the model in iterative training and
validation of individual electronic components.
