Waste to emerging and sustainable wealth: An integrated mining 4.0-recycling 4.0-decision making 4.0 framework overcoming greener red mud recycling technologies promotion

This study presents a comprehensive, three-phase framework for selecting an optimal technological solution for repurposing Red Mud (RM) based on a green mining approach. The framework introduces a novel ZE-FSIWEC method in Phase 1 for Mining 4.0 criteria weighting. In Phase 2, Fuzzy-Delphi method (FDM) screens key Recycling 4.0 alternatives, followed by a combination of eight multi-criteria decision-making (MCDM) methods including ARLON (2024), RAWEC (2024), MARA (2022), COBRA (2022), RAFSI, MAIRCA, MABAC, and ARAS for ranking. To address uncertainties, enhance decision reliability, and improve group decision credibility, fuzzy ZE-numbers are merged with Decision-Making 4.0 methods, which are then consolidated using Borda-count and Copeland ranking for a robust assessment. Iran was chosen as the analysis subject, with Phase 1 evaluating the national participants' perspectives, and Phase 2 focusing on the local site participants' viewpoints. In the final phase, the framework culminates in the development of a quantifiable RM Management Sustainability Score (RMMSS) to identify the most suitable strategic supply planning of RM residues among different Recycling 4.0 technologies and enhance mining waste management standards. Therefore, the proposed tech-paradigm based framework demonstrates its efficiency in a scenario where mining enterprises aim to market their RM. Sensitivity analysis shows the reliability of ZE-FSIWEC-ZE-RAWEC method, with a Spearman's correlation over 86.9 %, making it promising for future research. The Jajarm alumina complex case study showcases the framework's remarkable impact. This framework demonstrates its practicality and region-independent adaptability, contributing to a greener future by promoting sustainable practices and transforming hazardous RM waste into valuable assets. • Evaluating 15 different Recycling 4.0 technologies ranks for cleaner RM consumption. • Determining 18 various Mining 4.0 criteria weights using a hybrid ZE-FSIWEC method. • Embedding Decision-Making 4.0 across all framework phases considering uncertainty-reliability-group decision credibility. • Introducing a quantifiable RMMSS and certifications for greener mining waste management. • Consolidating 8 ZE-MCDMs using Borda-count & Copeland ranking for optimal RM utilization.