MASTER Assignment
Digital Product Passports: A Reference Architecture for EEE Supply Chains
Type : Master M-BIT
Period: March - August, 2025
Student : Kunapareddy, J.N.I. (Jhansi Naga Indusri, Student M-BIT)
Date Final project: August 27, 2025
Supervisors:
Abstract:
The increasing need for transparency, traceability, and sustainable practices in supply chains, most importantly the need transition from liner economy to circular economy, has driven the development of Digital Product Passports (DPPs). These structured digital records are designed to capture key product lifecycle data, from raw material sourcing to end-of-life management and support the transition to a circular economy. This thesis investigates the role of DPPs in reducing information asymmetry specially in the middle-of-life (MoL)/ Usage phase of IoT-enabled Electrical and Electronic Equipment (EEE), and proposes a validated reference architecture to guide their effective implementation for which mostly DPP is still a raising topic and industry experts are finding it difficult to understand the what exactly DPP means for them and as a whole ecosystem. This research begins with a detailed literature review of DPPs, analyzing definitions, regulatory guidance, EU Regulation, Expert Opinions by DPP Providers, data requirements, and architectural needs. The study acknowledges that while DPPs hold significant promise, their successful integration into existing EEE supply chains requires both technical and organizational enablers. To address this challenge, the thesis proposes a dedicated reference architecture specifically designed for DPP integration in EEE supply chains. This architecture incorporates principles from enterprise architecture and data mesh models, emphasizing secure data sharing, role-based access control, trust building, and modular design. The reference architecture is evaluated using a structured validation phase, involving expert feedback through questionnaires and semi-structured interviews. The validation focused on three key aspects: usefulness, quality, and variability along with business related questions section which focuses on business perspective. Results confirmed the model’s strength in aligning business and technical roles, enabling traceability, and supporting real-world implementation. However, limitations were identified since most notably the lack of inclusion of key MoL actors in the validation process, like repairers and refurbishers, who are critical for making DPPs truly useful in the reuse and refurbishment stages. Additionally, the study highlights that the successful adoption of DPPs depends not only on technology but also on organizational readiness, governance, and collaboration within the ecosystem. Feedback from participants emphasized the need for dedicated DPP teams, simplified architectural visuals for non-technical users and a personnel who fully understands complete DPP ecosystem is the key for coordinating this, and the inclusion of all lifecycle actors to ensure practical implementations. Key challenges identified include unclear regulatory guidance in the EEE sector specially, concerns about data confidentiality, and the absence of standardized data-sharing frameworks across industries. This thesis contributes to practice by delivering a validated reference architecture tailored for DPP adoption in the EEE sector. It offers a structured approach to lifecycle data management, supports ecosystem-wide collaboration, and provides a reusable framework for organizations aiming to meet circular economy targets. It also contributes to academic literature by exploring the intersection of data architecture, enterprise modeling, while demonstrating how expert validation can be applied to architectural research.
A key limitation of this research is that the reference architecture was not tested in a live organizational setting, leaving its practical applicability unverified. In addition, some perspectives mainly particularly those of downstream stakeholders such as repairers and refurbishers were missing in the validation phase. Future research should aim to pilot the architecture in real-world projects, expand validation to include MoL actors like repairers and refurbishers and other downstream partners, and evaluate the impact of DPP adoption on operational efficiency and sustainability outcomes. Updates maybe needed as regulatory frameworks evolve and best practices for DPP implementation become more widely established.
In conclusion, the thesis offers both conceptual and potential for practical contributions, it clarifies the role and scope of DPPs in supporting circular economy goals and presents a validated architectural approach for their adoption in the EEE sector. Future work should focus on extending the architecture to incorporate external MoL actors and testing it in real-world pilot projects to assess its scalability and impact. The research demonstrates that when implemented with the right architectural and governance structures, DPPs can significantly reduce information asymmetry and enable more sustainable, data-driven supply chain practices.