About PSS-Pass
Shaping a Sustainable Future with Digital Product-Service Ecosystems
The Digital Product Passport (DPP) is a new concept of a policy tool designed to help achieve a circular economy (CE). In its initial design, the DPP is intended to compile product information, primarily from manufacturers, to help create more circular products. This requires a standard framework to ensure all DPPs are consistent and compatible.
Modern industrial companies are moving beyond selling just products; they are adding services as key value-added activities. In this model, the product is just one part of the total offering—a shift that enables new business models like “pay-per-use” and “pay-per-results.”
This approach falls under the concept of a Product Service System (PSS). A major benefit of PSS, besides radically improving how products are used, is a reduction in the environmental footprint of both the products and the services. However, the total environmental impact of PSS still needs deeper investigation, especially as the services around products become increasingly digital.

Digitalization and services are merging, leading to the Smart Product Service System (Smart PSS). The services within PSS are a vital, yet underused, source of (often digital) data about the product and how it’s used.
Using digital tools to consistently “track and trace” data—such as the origin, materials, and complete lifecycle of a product and all related services (like maintenance records, component substitutions, and failure causes)—will be a key factor in achieving full circularity in manufacturing.
The PSS-Pass Project Objectives
The main goal of the PSS-Pass project is to explore how extending the existing DPP concept into a Digital Product Service System Passport (DPSSP) can be done effectively, and how this new passport will boost the manufacturing industry’s circularity.
The project’s central idea is that the DPSSP will provide crucial new insights into the sustainability potential of both products and services. For example, the overarching hypothesis is that using Life Cycle Assessment (LCA), supported by Machine Learning (ML) methods and fed with real-time data, will lead to more accurate LCA results and better life cycle decision-making.
The collected and shared data from the DPSSP will make it possible to effectively use ML for more reliable circularity decisions for PSS. Recognizing that the DPSSP concept will likely increase complexity, the project intends to offer an innovative solution for the DPSSP and associated simulation and decision-support tools for companies already using PSS and those planning to adopt it.
The project will deliver:
A Methodological Framework for creating and updating the DPSSP.
A Digital Environment for the DPSSP, based on current technology standards.
A set of Ontologies (structured data models) to improve compatibility within the DPSSP Environment.
A new DT-based Simulation Framework for modeling standardized and compatible Digital Twins for PSS lifecycle analysis.
An AI-based method/tool to forecast the environmental impact of PSS.
Our Pilots

Aiming to demonstrate that the PSS-Pass solutions are built based on and are applicable to a wide scope of industries.
Pilot 1
Sector – Home appliances

Pilot 2
Sector – Complex equipment

Pilot 3
Sector – Textile

