DMaaST | Innovative modelling and assessment capabilities through MaaS for Manufacturing Ecosystem resiliency

Summary
DMaaST aims to enhance the manufacturing ecosystem's resiliency and capability of self-adaptation in response to external events. It is achieved through a Smart Manufacturing Platform comprising 4 layers: The data layer establishes a foundation for mapping manufacturing ecosystem information using ontologies and decentralized knowledge graphs, ensuring a trusted cross-organization real-time data integration. Next, a layer with a two-level cognitive digital twin is created, with the low-level DT modelling two use cases' manufacturing services production line; and the high-level DT modelling the main stages of use-cases’ sectors value chains. The resulting DTs will use human expertise-knowledge, data-driven algorithms and physical modelling to provide a reliable and robust DT of the manufacturing ecosystem. The next layer employs the data and modelling layer's information to present a multi-objective distributed decision support system algorithm combining multi-objective techniques and the latest trends in Federated Deep Learning. This makes DTs actionable models and provides the necessary information to make optimal production decisions. The fourth layer focuses on presenting the information in a user-friendly manner with timely scoreboards. Additionally, a dedicated module will assess the production's circularity and sustainability and considering products traceability through the EU-DPP. Therefore, the sustainability and remanufacturing opportunities of the production process will be improved. The project ensures scalability, providing information for replicating and trying new manufacturing processes thanks to the manufacturing services digital warehouse while assessing risks and opportunities for improvement. DMaaST innovations enable the manufacturing ecosystem to adopt the Manufacturing as a Service concept by smoothly evolving all the technologies from a TRL3 to a consolidated TRL6 in 2 use cases in key sectors, aerospace and electronics.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101138648
Start date: 01-05-2024
End date: 30-04-2028
Total budget - Public funding: 5 862 752,50 Euro - 5 862 752,00 Euro
Cordis data

Original description

DMaaST aims to enhance the manufacturing ecosystem's resiliency and capability of self-adaptation in response to external events. It is achieved through a Smart Manufacturing Platform comprising 4 layers: The data layer establishes a foundation for mapping manufacturing ecosystem information using ontologies and decentralized knowledge graphs, ensuring a trusted cross-organization real-time data integration. Next, a layer with a two-level cognitive digital twin is created, with the low-level DT modelling two use cases' manufacturing services production line; and the high-level DT modelling the main stages of use-cases’ sectors value chains. The resulting DTs will use human expertise-knowledge, data-driven algorithms and physical modelling to provide a reliable and robust DT of the manufacturing ecosystem. The next layer employs the data and modelling layer's information to present a multi-objective distributed decision support system algorithm combining multi-objective techniques and the latest trends in Federated Deep Learning. This makes DTs actionable models and provides the necessary information to make optimal production decisions. The fourth layer focuses on presenting the information in a user-friendly manner with timely scoreboards. Additionally, a dedicated module will assess the production's circularity and sustainability and considering products traceability through the EU-DPP. Therefore, the sustainability and remanufacturing opportunities of the production process will be improved. The project ensures scalability, providing information for replicating and trying new manufacturing processes thanks to the manufacturing services digital warehouse while assessing risks and opportunities for improvement. DMaaST innovations enable the manufacturing ecosystem to adopt the Manufacturing as a Service concept by smoothly evolving all the technologies from a TRL3 to a consolidated TRL6 in 2 use cases in key sectors, aerospace and electronics.

Status

SIGNED

Call topic

HORIZON-CL4-2023-TWIN-TRANSITION-01-07

Update Date

22-12-2024
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Factories of the Future Partnership - Made in Europe Partnership

Made in Europe (MiE)
HORIZON-CL4-2023-TWIN-TRANSITION-01
HORIZON-CL4-2023-TWIN-TRANSITION-01-07: Achieving resiliency in value networks through modelling and Manufacturing as a Service (Made in Europe Partnership) (RIA)
Specific Objective 1: Excellent, responsive and smart factories & supply chains
R&I Objective 1.1: Data ‘highways’ and data spaces in support of smart factories in dynamic value networks
HORIZON-CL4-2023-TWIN-TRANSITION-01-07: Achieving resiliency in value networks through modelling and Manufacturing as a Service (Made in Europe Partnership) (RIA)
R&I Objective 1.4: Artificial intelligence for productive, excellent, robust and agile manufacturing chains - Predictive manufacturing capabilities & logistics of the future
HORIZON-CL4-2023-TWIN-TRANSITION-01-07: Achieving resiliency in value networks through modelling and Manufacturing as a Service (Made in Europe Partnership) (RIA)
Horizon Europe
HORIZON.2 Global Challenges and European Industrial Competitiveness
HORIZON.2.4 Digital, Industry and Space
HORIZON.2.4.0 Cross-cutting call topics
HORIZON-CL4-2023-TWIN-TRANSITION-01
HORIZON-CL4-2023-TWIN-TRANSITION-01-07: Achieving resiliency in value networks through modelling and Manufacturing as a Service (Made in Europe Partnership) (RIA)
HORIZON.2.4.1 Manufacturing Technologies
HORIZON-CL4-2023-TWIN-TRANSITION-01
HORIZON-CL4-2023-TWIN-TRANSITION-01-07: Achieving resiliency in value networks through modelling and Manufacturing as a Service (Made in Europe Partnership) (RIA)