## 3 Results
### Traceability Framework Capabilities  
The extended WEave framework successfully recorded and linked data across the entire product lifecycle in our simulations. For apparel products, we were able to trace a finished garment back to its raw materials (as in the original design) and forward into its post-use fate. For example, consider a specific garment with ID GARMENT_001. Using the TraceProductHistory chaincode function (augmented as described), an auditor could trace a record showing:  
* Garment GARMENT_001 was produced in Order #1001 on 1 March 2025, using Fabric Roll FAB_456 and Trim batch TRIM_789. * FAB_456 was made from RawMaterial lots COTTON_123 (virgin cotton, 5 kg) and RCOTTON_001 (recycled cotton, 1 kg). * RCOTTON_001 is a recycled material lot created on 20 February 2025 from Returned Product USED_GARMENT_042. * USED_GARMENT_042 corresponds to an apparel item originally produced in Order #980 on 15 June 2024 (a previous lifecycle), which was returned by Retailer X on 1 February 2025 and then recycled by RecyclerCo on 20 February 2025. This chain of information demonstrates a closed-loop trace: one product's origin includes material from a previous product. All relevant events (production, return, recycle, reuse) are immutably stored on the ledger. This level of traceability addresses the generally identified needs for making product lifecycle information available to enable circular economy practices. Regulators could verify recycled content (e.g., seeing that 1 kg out of 6 kg of input is recycled cotton, thus \(\sim\)16% recycled content for that garment). Similarly, if a question arises about whether recycling took place for returned items, the ledger provides proof (each returned item has a recorded outcome). All participants with the appropriate permissions could access the status of returns and recycling. In our scenario, the retailer (RE) and auditor (AU) could query how many products were returned and what happened to them. This is important for accountability--for instance, if the company pledges to take back products and recycle 50% of them, the blockchain provides a verifiable audit trail of those numbers. The auditor agent was able to confirm that count via a simple range query on all ReturnedProduct assets and all RecycledMaterial assets. In a real deployment, this could feed into sustainability reports or compliance reports (for legislation like extended producer responsibility). We observed that including the Recycler (RC) node in the network did not hinder multi-party collaboration; in fact, it enhanced data sharing. For example, the raw material supplier (RM) could trust the quality of RCOTTON_001 in its second life because it was tied to known sources, and presumably, the recycler's process is certified. In the simulation, we did not explicitly simulate quality variation in recycled fiber, but the framework could be extended to include quality metrics (e.g., fiber strength) on the recycled lot asset. The key point is that the blockchain acts as a single source of truth that all supply chain actors (including those in reverse logistics) refer to. This aligns with industry findings summarized by a 2024 KPMG report that digitalization improves visibility and thus supply chain resilience [41]--here, visibility extends to returned goods, which are often a blind spot in traditional systems. In the furniture scenario simulation, we were able to reuse much of the same chaincode structure with minor adjustments. The framework proved adaptable to a different supply chain topology (multiple component suppliers feeding an assembly plant). The closed-loop concept also held, e.g., a batch of X was traced into new production of Y. This suggests the WEave framework can serve as a template for various sectors aiming to implement blockchain traceability with circular loops. Rather than designing a new solution from scratch, practitioners could take our fabric chaincode and adapt asset definitions and transaction flows to their product's specifics.