Project cooperationUpdated on 16 July 2025
Reverse value chain for circular electronics management - supported by postal networks
Circular economy and value chains consultant at Universal Postal Union (UPU)
London, United Kingdom
About
My project team at the UPU is working to implement reverse value chain models for circular electrical and electronic eqiupment (EEE) management, but supported by postal operators. The ideation stems from realising the missed opportunity from not sufficiently utilising postal operators' already existing phyiscal infrastructure suited for reverse logistics (RL), as well as technological and digital capacities for product tracing and related data management.
From the preliminary research phase, we have identified viable business models, policy incentives and gaps, and service diversification pathways for a range of EEE stakeholders, spanning not only postal operators, but also producers/manufacturers, producer responsibility organisations (PROs), repair/refurbishment organisations, and more.
Within this context, we would like to research further what are the most feasible data technologies are that can enhance reverse value chain traceability, automation, and predictability. For instance, they can be about: implementing DPP for used EEE subject to refurbishment and materials recovery; setting up user platforms for booking on-demand EEE collection; interoperable data ecosystems for availing product and materials recylability/repairability information, and so on.
If you are already working on those technology areas, or broadly on operationalising consumer product reverse value chains, please get in touch and we can discuss potential collaboration!
Stage
- Early idea
- Already defined
Topic
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Enabling technologies | Network design of reverse supply chains
Type
- Consortium seeks Partners
Attached files
Organisation
Similar opportunities
Project cooperation
- Early idea
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
Rebecca Pahmeyer
Research Scientist at Fraunhofer IPA
Stuttgart, Germany
Project cooperation
- Early idea
- Already defined
- Consortium seeks Partners
- Enabling technologies | Robotic / handling - and assistance systems
- Enabling technologies | (Advanced) Materials and additive manufacturing
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
Athina Kotrozou
Student
Stuttgart, Germany
Project cooperation
- Already defined
- Consortium seeks Partners
- Enabling technologies | Robotic / handling - and assistance systems
- Enabling technologies | (Advanced) Materials and additive manufacturing
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
Angeles Ibaibarriaga
Founder at Segunda Generación SpA
Lolol, Chile