This chapter evaluates the proposed Redundancy-hardened Robust Fusion System (R2FS) on real-world use cases, focusing on its performance and capabilities. The evaluation is carried out along the three main contributions of the book: the Dual Possibilistic Redundancy Metric (DPRM), design algorithms for redundancy-orchestrated fusion topologies, and robustness-hardened fusion rules. The results demonstrate the qualitative advantages of the DPRM in handling incomplete information, confirm the practicality of DPRM-based topology design under non-representative data, and show the superior robustness of redundancy-orchestrated topologies combined with the newly proposed fusion rules. Overall, the chapter provides empirical evidence that R2FS outperforms traditional approaches, particularly in scenarios affected by epistemic uncertainty and defective information sources.