Decision‑making framework for prioritizing digital twin sensor parameters with application in the aviation sector

This paper proposes a structured decision-making framework for supporting Digital Twin implementation by integrating Fuzzy Decision-Making Trial and Evaluation Laboratory with the Technique for Order of Preference by Similarity to Ideal Solution. The framework is applied to the aviation sector as a case study, focusing on the transition toward circular economy practices. The methodological contribution lies in formalizing and weighting key benefits and challenges of Digital Twin adoption, followed by a structured ranking of enabling sensor parameters. Grounded in literature analysis and expert input, this framework offers managerial and strategic decision support under uncertain conditions. The findings of this study confirm the framework’s ability to prioritize critical factors and such sensor parameters as motion sensors, essential components for monitoring human movement and detecting unauthorized access to restricted areas within aviation facilities. Diverse scenarios of sensitivity analyses have been conducted by formalizing multiple weighting scenarios for the most significant benefits and challenges, reinforcing the reliability of the outcomes. Beyond the aviation sector, the framework has the potential to be extended to other industries, providing a strategic tool for guiding Digital Twin-sensor prioritization in complex operational environments.