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.

翻译：由于科技产品的快速迭代和众多信息技术领域的激烈竞争，电气电子设备废弃量持续增长。每年数百万吨电子垃圾被排入环境，对人类健康造成严重影响。因此，利用技术手段控制此类废物流至关重要，特别是通过人工智能技术以及关键原材料的回收再利用来支持新的生产过程。本文聚焦于运用数学创新模型度量废弃印刷电路板中电子元件的可回收性。该创新方法同时评估废弃电子元件的可回收性与回收难度，并集成AI模型以优化拆解分拣流程。通过评估印刷电路板上单个电子元件的可回收性，既可揭示有价值材料的回收潜力，又能从经济价值和生产效用维度反映回收过程的复杂程度。这种新颖的度量方法有助于AI模型在废弃电路板自动拆解过程中精确确定待识别与分拣的类别数量，同时支持模型对单个电子元件进行迭代训练与验证。