Periodic Reporting for period 1 - MATISSE (Model-based engineering of Digital Twins for early verification and validation of Industrial Systems)
Reporting period: 2024-09-01 to 2025-08-31
MATISSE addresses the growing need for reliable methods to design, validate, and deploy Digital Twins (DTs) in complex industrial systems. Current DT solutions are fragmented, lack interoperability, and demand high manual effort for verification and validation across the system life cycle. The project responds to this gap by developing a model-based engineering framework that supports continuous design, testing, and integration of DTs in safety-critical and resource-intensive sectors.
The project aims to deliver:
1) A structured method for requirements-driven DT engineering.
2) A conceptual and technical architecture enabling traceability from use case needs to DT solutions.
3) Services for automated testing, monitoring, and prediction of system qualities.
4) Integrated demonstrators showing measurable efficiency and reliability gains across real industrial cases.
The expected impact concerns higher trust in DT adoption, reduced development cost, earlier fault detection, and stronger alignment with European strategies on digital transformation, cyber-physical resilience, and green industry. The first results already place the project in dialogue with policy agendas on trustworthy AI, standardisation of industrial data spaces, and strategic autonomy in microelectronics.
Social sciences and humanities contribute through methods for eliciting stakeholder requirements, ethical analysis of data governance, and studies of organisational readiness for DT uptake.
The project aims to deliver:
1) A structured method for requirements-driven DT engineering.
2) A conceptual and technical architecture enabling traceability from use case needs to DT solutions.
3) Services for automated testing, monitoring, and prediction of system qualities.
4) Integrated demonstrators showing measurable efficiency and reliability gains across real industrial cases.
The expected impact concerns higher trust in DT adoption, reduced development cost, earlier fault detection, and stronger alignment with European strategies on digital transformation, cyber-physical resilience, and green industry. The first results already place the project in dialogue with policy agendas on trustworthy AI, standardisation of industrial data spaces, and strategic autonomy in microelectronics.
Social sciences and humanities contribute through methods for eliciting stakeholder requirements, ethical analysis of data governance, and studies of organisational readiness for DT uptake.
During RP1 the project advanced in line with the Grant Agreement.
WP1 defined industrial requirements and produced the initial architecture of the MATISSE framework, supported by two internal hackathons and structured traceability modelling.
WP2 delivered a Multivocal Literature Review on DT engineering and the first version of the conceptual framework. Work on the technical infrastructure started with the preparation of D2.3.
WP3 began at Month 10, defining test generation strategies, predictive metrics, and data pipelines for smart quality assessment.
WP4 set the integration plan and prepared lightweight versions of the use cases to support early validation.
WP5 delivered the project brand, website, newsletters, monitoring tools, and first versions of the Dissemination and Exploitation Plans.
WP6 ensured governance, risk control, reporting, and two plenary meetings. All mandatory deliverables were submitted.
Scientific output so far includes 13 journal papers, 20 conference papers, and 6 workshop papers. Several tools are moving toward open-source release.
WP1 defined industrial requirements and produced the initial architecture of the MATISSE framework, supported by two internal hackathons and structured traceability modelling.
WP2 delivered a Multivocal Literature Review on DT engineering and the first version of the conceptual framework. Work on the technical infrastructure started with the preparation of D2.3.
WP3 began at Month 10, defining test generation strategies, predictive metrics, and data pipelines for smart quality assessment.
WP4 set the integration plan and prepared lightweight versions of the use cases to support early validation.
WP5 delivered the project brand, website, newsletters, monitoring tools, and first versions of the Dissemination and Exploitation Plans.
WP6 ensured governance, risk control, reporting, and two plenary meetings. All mandatory deliverables were submitted.
Scientific output so far includes 13 journal papers, 20 conference papers, and 6 workshop papers. Several tools are moving toward open-source release.
The project delivers three advances:
1) Model-based DT engineering chain linking requirements, architecture, and validation assets through formal traceability.
2) Smart verification services that exploit DT models for automated test generation, fault localisation, and predictive quality assessment.
3) Multi-partner integration approach enabling heterogeneous tools to interoperate within a shared reference architecture.
To secure further uptake, the next steps include:
- maturation of TRLs through demonstrators in transport, manufacturing, and energy,
- alignment with emerging standards on DT federation,
- assessment of exploitation routes for open-source and commercial assets,
- access to finance for post-project industrialisation, and
- support for IPR and licensing strategies within the consortium.
1) Model-based DT engineering chain linking requirements, architecture, and validation assets through formal traceability.
2) Smart verification services that exploit DT models for automated test generation, fault localisation, and predictive quality assessment.
3) Multi-partner integration approach enabling heterogeneous tools to interoperate within a shared reference architecture.
To secure further uptake, the next steps include:
- maturation of TRLs through demonstrators in transport, manufacturing, and energy,
- alignment with emerging standards on DT federation,
- assessment of exploitation routes for open-source and commercial assets,
- access to finance for post-project industrialisation, and
- support for IPR and licensing strategies within the consortium.