Updated on 22 May 2025
Digital product passport and sustainable consumption
About
Digitalisation offers a wide range of opportunities to make consumption more sustainable for society as a whole and to support consumers in their purchasing decisions towards sustainable alternatives.
The main functional potential of the DPP as a cross-product and standardised data set is to collect data from the entire product life cycle and make it accessible to various stakeholders, including consumers and and therefore has great potential to promote sustainable consumption decisions.
Similar opportunities
Project cooperation
Digital Product Passport for Circular Economy
- Already defined
- Expertise offered
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Data technologies | Design of an adaptable Digital Product Pass:
- Enabling technologies | (Advanced) Materials and additive manufacturing
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- 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 | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- 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)
Ralph Weissnegger
Director Innovation & Funding at CISC Semiconductor GmbH
Klagenfurt, Austria
Project cooperation
- Early idea
- Expertise offered
- Consortium seeks Partners
- Data technologies | (AI based) process and system control technologies
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- 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)
Krikamol Muandet
Chief Scientist and Faculty Member at CISPA - Helmholtz Center for Information Security
Saarbrücken, Germany
Project cooperation
AI-Driven Circular Fashion Digital Paltform: MODA App
- Early idea
- Consortium seeks Partners
- Enabling technologies | Network design of reverse supply chains
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
Murat Demir
Asst. prof.dr at Dokuz Eylül University Textile Engineering
Izmir, Türkiye