Multi-Criteria Trade-Off Analysis of Dry Particle Size Classification Technologies for Lunar Regolith Processing

Kurzfassung

Renewed interest in long-duration lunar exploration has driven the development of in-situ resource utilisation technologies to reduce reliance on Earth-supplied materials. Effective particle size classification of lunar regolith is one of the critical beneficiation steps for the selective preparation of feedstock to improve the performance of downstream extraction and utilisation systems. Fluid-based classification methods, that are generally used for terrestrial applications, are unsuitable for the lunar environment making dry processing technologies the only viable approach. Building on prior experimental campaigns that have established the feasibility and performance characteristics of a range of dry particle size classification technologies, this study presents a systematic trade-off analysis to comparatively evaluate and rank competing approaches under a unified multi-criteria framework. This framework consists of 13 evaluation parameters weighted to reflect the operational priorities of lunar regolith processing. A one-at-a-time sensitivity analysis across 26 perturbation scenarios was conducted to assess the robustness of the ranking outcomes. The Rotary Sieve (RS) was identified as the most promising technology, achieving the highest weighted aggregate score and retaining the top rank across all evaluated scenarios, demonstrating the robustness of this outcome to variations in the assigned parameter weights. The multi-criteria evaluation framework developed in this study serves as a living reference instrument for dry particle size classification technology selection, providing a transparent and updatable basis for future assessments as experimental data and higher-fidelity operational information become available, supporting the long-term technology maturation roadmap for lunar ISRU architectures.