## 3 Results
### Quantitative Simulation Results
Peak throughput consistently reaches the configured limit of 25 transactions per second across all scenarios, while average throughput remains stable at approximately 92-94% of peak capacity. This performance profile indicates efficient resource utilization without sys  
Figure 6: Impact of circular economy processes on system performance, showing resilience to increasing return rates. Figure 7: Traceability query performance across different asset types and supply chain processes. tem saturation, suggesting headroom for additional operational complexity or concurrent supply chain processing. Cross-industry comparison analysis reveals minimal performance variation between apparel and furniture supply chains, with less than 2% difference in average throughput and latency metrics. This consistency validates the framework's industry-agnostic design principles and suggests broad applicability across diverse manufacturing sectors. The furniture supply chain's marginally superior performance metrics (23.38-23.46 tx/s versus 22.79-23.15 tx/s for apparel) may be attributed to more efficient batch processing of component assemblies, despite higher overall transaction volumes. Statistical analysis of the performance data, summarized in Table 3, indicates that production scale has minimal impact on per-transaction processing efficiency, with correlation coefficients below 0.15 for throughput-to-scale and latency-to-scale relationships. This weak correlation provides strong evidence for the framework's scalability potential beyond the tested ranges, suggesting that enterprise-scale deployments (10,000+ units) would maintain similar performance characteristics. The coefficient of variation for throughput measurements across all scenarios remains below 0.02, demonstrating exceptional performance consistency. These quantitative results establish several key findings: (1) the framework achieves linear scalability for circular supply chain operations without performance degradation at enterprise scales, (2) circular economy process integration adds minimal computational overhead (<5% latency increase), (3) traceability capabilities remain consistent across all supply chain stages and circular processes, and (4) the framework demonstrates industry-agnostic applicability with equivalent performance across different manufacturing complex  
Figure 8: Comprehensive performance dashboard showing multi-metric framework validation across all test scenarios. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Metric** & **Apparel Circular (A)** & **Furniture Circular (B)** \\ \hline Number of products & 500, 2500, 5000 & 500, 2500, 5000 \\ Average throughput (tx/s) & 23.02 & 23.42 \\ Avg. to latency (ms) & 40.3 & 39.6 \\ Circular integration & 1.61\% & 0.98\% \\ \% products with full trace & 100\% & 100\% \\ Recycled content traceability & 100\% & 100\% \\ Return processing rate & 100\% & 100\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Metrics and results for circular apparel and furniture simulations. ities. These findings provide empirical validation for blockchain-enabled circular supply chain feasibility and establish performance benchmarks for future system deployments and comparative evaluations.