Optimal, reliable, and sustainable technology selection for mining overburden waste utilization using green & climate-smart mining (GCSM): A hybrid fuzzy multi-criteria decision-making tool

Abstract

This study presents green and climate-smart mining (GCSM), a holistic sustainability tool leveraging Industry 4.0 technologies for mining waste management. It proposes a three-step GCSM assessment framework to ensure reliable, clean, and sustainable overburden waste management. Iran was considered as a case study. In step 1, GCSM categories and criteria were evaluated using the Randomized Weighted Fuzzy-Analytical Hierarchy Process (RWFAHP, 2024) through the national experts' viewpoints. Step 2 applied the Fuzzy Delphi method (FDM) to find key factors for evaluating emerging GCSM technology alternatives. Then, alternatives' ranks were determined to identify the best strategic supply planning of overburdens by local mine experts using a combination of recent Multi-criteria decision-making (MCDM) methods and fuzzy extended Z-numbers (ZE-numbers) to enhance group-decision credibility, uncertainty, and reliability. For robust assessment, MCDM methods including RAWEC (2024), CRADIS (2022), MARCOS, COCOSO, CODAS, VIKOR, and TOPSIS were employed. Finally in step 3, by combining the results of steps 1–2, a quantifiable parameter of GCSM Management Sustainability Score (GCSMMSS) was introduced to practically enhance mining standards. For an illustrative example, the Goharzamin mine was selected to obtain the optimal technology for the reduction, reuse, and recycling of iron ore overburden (IOO) residues. The ZE-RAWEC method, outperforming other ZE-MCDMs, is reliable for future applications. This framework is a practical, efficient, and versatile Industry 4.0 solution, enabling the effective overburden management and supporting mining geomaterial administration systems for a greener earth.