Multi-Criteria Decision Support for Sustainable Supplier Evaluation in Mining SMEs: A Fuzzy Logic and TOPSIS Approach

Background: Improving operational efficiency in the mining industry increasingly de-pends on a mature asset management framework and the careful selection of reliable, sustainable suppliers for systems, personnel, equipment, and services. Given the complexity of mining operations and the growing use of digital tools, choosing the right maintenance management system requires a robust decision-making process that considers economic, environmental, and social sustainability factors. Methods: This study develops and compares two multi-criteria decision-making approaches, a ranking method and a fuzzy logic-based model to evaluate four maintenance management systems against fifteen sustainability-related criteria. Expert opinions from executives and operational managers in the South African mining sector were gathered, focusing on factors such as cost, integration, reliability, ease of use, inventory control, and predictive capabilities. Results: The ranking method produced a clear, quantitative order of preference, while the fuzzy model addressed uncertainty and subjectivity in expert judgments. Both methods identified the same top choice: UPKEEP, followed by SAP, FIIX, and LIMBLE. Conclusions: This comparison shows that combining fuzzy logic with sustainability-focused evaluation can improve the flexibility and reliability of supplier selection in asset management. The proposed approach offers practical guidance for aligning maintenance system choices with broader sustainability goals in mining operations.