Barriers to circular supply chain implementation in drilling mud recycling: a hybrid multi-criteria decision-making framework for petroleum engineering applications

Drilling-mud recycling supports resource recovery and environmental management, but circular supply chain implementation is constrained by barriers that are difficult to prioritize under uncertain expert judgments. This study develops a multi-criteria decision-making (MCDM) framework integrating interval-valued Fermatean fuzzy sets (IVFFSs), the Best–Worst Method (BWM), and Ranking of Alternatives through Functional Mapping of Criterion Sub-Intervals into a Single Interval (RAFSI). Five specialists evaluated ten barriers against six criteria. Separate IVFFS-BWM models were solved for each expert, and the resulting criterion weights were averaged. IVFFS-RAFSI was then applied to each expert’s barrier assessments, followed by aggregation of the final scores and cross-expert sensitivity analysis. Cost, implementation time, and technical complexity received the highest criterion weights. Technological limitations, insufficient infrastructure, and process complexity and uncertainty obtained the highest mean barrier scores. These three barriers showed less score dispersion across experts than financial and regulatory barriers. The contribution lies in integrating expert-specific weighting, barrier prioritization, and cross-expert robustness assessment within a structured workflow tailored to circular drilling-mud supply chains. The findings support prioritizing technological upgrading, infrastructure development, and process stabilization in the analyzed context. The five-expert, single-country application warrants further validation using broader expert panels and operational performance data.