Research Project
PSS-Pass: methods and tools supporting digital product service system passport
From Digital Product Passport (DPP) to Digital Product Service System Passport (DPSSP): PSS-Pass leverages AI and Digital Twin to provide decision support for the circular economy for manufacturing industry.
Where: international
Where: international
Challenge
The DPP, introduced with the recent Ecodesign for Sustainable Products Regulation of EU, aims to promote a lower environmental impact through access to data on the whole value chain. Manufacturing companiesneed to move to new business models, extending their offering to additional services, such as maintenance services.
Approach
Through techniques that combine digital twin, simulation, data analytics and machine learning, PSS-Pass would guarantee a more accurate Life Cycle Assessment, while supporting the decision-making process over the entire life cycle. The collected and shareable data by the DPSSP will allow Machine Learning to be effectively applied for more reliable decision-making processes.
Digital Ecosystem
Solution
Digital Ecosystem
PSS-Pass proposes a digital environment, tools and methodologies to extend the purposes of the Digital Product Passport to the Smart Product Service Systems, through the use of AI, Digital Twins and Data Analytics. The proposed solutions enable data sharing within Data Spaces and serve as a basis for the Digital Product Service System Passport (DPSSP). The solutions is validated in three use cases related to the production of household appliances, precision and complex manufacturing equipment and the textile sector. ENG is responsible for the development of simulation tools through Digital Twins and the integration of the DPSSP to industrial Data Spaces.
The project has received co-funding from the Horizon Europe programme - Contract No. 101177594.
Co-funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. The European Union cannot be held responsible for them.
Results
Simplification of LCA and due diligence
Environmental impact monitoring
Maximising impact in manufacturing
Impacts
Technologies
AI & Data
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