Sustainable development and circular economy require balancing between environmental, economic and social benefits and de-coupling the economic growth from resource use. The European New Green Deal highlights the need for reliable, comparable and verifiable sustainability information. Existing sustainability assessment approaches suffer from lack of comprehensiveness, consistency and practical tools for implementation. This results in fragmented and hardly comparable information on product sustainability performance. The ORIENTING project takes up this challenge and develops a robust and operational methodology for the life cycle sustainability assessment (LCSA) of products and services. The novelty value of the project relates to an approach that considers environmental, social and economic impacts in an integrated way. The ambition is to develop a methodology that can assess goods produced under linear as well as circular business models, allowing practitioners to understand and manage possible trade-offs. ORIENTING contributes to the development of a future Product Sustainability Footprint at European level, evolving existing PEF and designing new indicators for the evaluation of material criticality and product circularity. New tools will be developed to support and simplify the methodology application in business and policy development. Tools include guidance and training materials, data and software specifications and a hands-on LCSA IT tool. The LCSA methodology and its enabling tools are demonstrated in five industrial case studies. The consortium works in close cooperation with various stakeholders (industry associations and clusters, SMEs, consumer organisations, as well as governmental and standardisation bodies). The project outcomes will enable informed business decisions and contribute to the development of a levelled playing field – a single market – for products based on robust (i.e. transparent and verifiable) sustainability information.

Modern industrial companies aim to extend their products with services as fundamental value-added activities. The key potential of the concept of Product Service System (PSS), besides radical improvements in the use of products, is a reduction of environmental footprint of products and services. The overall footprint of PSS is still insufficiently investigated. The services within PSS are an important, insufficiently used source of (digitalized) data on the product and its use. It is likely that digital means facilitating provision of consistent “track and trace” information on the origin, composition and entire life cycle not only of a product but of all services offered and used around the product, will offer important contribution towards achievement of full circularity for manufacturing. The key idea of PSS-Pass is to investigate how extension of DPP to Digital Product Service System Passport (DPSSP) can be effectively achieved and how it will allow for improved circularity of the manufacturing industry. The overarching hypothesis is that LCA underpinned by Machine Learning (ML) methods and informed by dynamic data paves the way to more accurate LCA while supporting PSS life cycle decision making. The collected and sharable data from DPSSP will allow to effectively apply ML as well as Digital Twin (DT) for more reliable decision-making processes concerning circularity of PSS. The project will provide Methodological Framework for definition, development and update of DPSSP, Digital Environment for DPSSP built on existing interoperability architectures, set of ontologies for improved interoperability at DPSSP Environment, novel DT-based Simulation Framework, for modelling standardized and interoperable DTs for PSS lifecycle analysis, and AI based method/tool to forecasts the environmental impact of PSS. The PSS-Pass solutions will be tested and evaluated within 3 pilots in diverse sectors: home appliances, complex equipment, and textile industry.