International Journal of Sustainable Engineering (Dec 2024)

AI-based decision support system for enhancing end-of-life value recovery from e-wastes

  • Ehsan Simaei,
  • Shahin Rahimifard

DOI
https://doi.org/10.1080/19397038.2024.2306293
Journal volume & issue
Vol. 17, no. 1
pp. 1 – 17

Abstract

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ABSTRACTThe growing diversity and volume of e-waste products are emerging as significant and complex challenges from environmental, economic, and recycling perspectives. This surge not only hampers the effective management and conservation of precious resources and strategically important materials (SIMs) but also intensifies the problem. Addressing this pressing global issue necessitates a holistic and intelligent decision-making model capable of effortlessly handling the vast variety and volume of e-waste products. This paper introduces a novel multi-criteria decision support system (DSS) that combines AI visual recognition with a multi-fuzzy model to precisely determine the optimal End-of-Life (EoL) recovery route. Additionally, the functionality of the proposed DSS is showcased through a pilot implementation and case study examples, emphasising the advantages of a fully automated, reliable, and efficient EoL management for e-waste.

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