Engineering Innovation in
Digital Industry
"Data as a Product" model for resilient factory 4.0.
Approach & Solution
Approach
As part of the green, circular and digital transformation of the European manufacturing community, it is extremely important that data-driven digital manufacturing processes incorporate innovative and active resiliency strategies both at production and supply chain levels.
This is fundamental to maintain their sovereignty and competitiveness, respecting European digital values to improve individual and value chain flexibility.
RE4DY demonstrates that the European industry can jointly build unique data-driven digital value networks 4.0 to sustain competitive advantages through digital continuity and sovereign data spaces across all phases of product and process lifecycle.
This is fundamental to maintain their sovereignty and competitiveness, respecting European digital values to improve individual and value chain flexibility.
RE4DY demonstrates that the European industry can jointly build unique data-driven digital value networks 4.0 to sustain competitive advantages through digital continuity and sovereign data spaces across all phases of product and process lifecycle.
Solution
RE4DY develops a self-service, qualified, smart, scalable, secure and semantic industrial Data-as-a-Product (DaaP) model for factories. It is integrated with an executable cognitive digital twin model through lighthouse value network trials in different sectors such as the automotive, aeronautical, mechanical and electric battery ones.
Engineering leads the Digital 4.0 continuum reference architecture and designs and provides federated learning capabilities. It also participates to the AVIO pilot wtih system integration and computer vision based solutions for anomaly detection.
The project has received co-funding from the Horizon Europe programme - Contract No. HORIZON-CL4-2021-TWIN-TRANSITION-01.
Engineering leads the Digital 4.0 continuum reference architecture and designs and provides federated learning capabilities. It also participates to the AVIO pilot wtih system integration and computer vision based solutions for anomaly detection.
The project has received co-funding from the Horizon Europe programme - Contract No. HORIZON-CL4-2021-TWIN-TRANSITION-01.
Results
Digital continuity and DaaP exploitation
Quality inspection and operators training accelerated by AI
Increased autonomy and interoperability of the factory 4.0
Reduced implementation costs
Democratised industrial data spaces and cognitive digital twins
Project value
Cost cutting
Innovation
Process performance
Enabling Technologies
AI Advanced Analytics
Cloud
Cybersecurity
Digital Twin
IoT
Engineering proprietary products & other technologies
ALIDA
DIHIWARE
FIWARE
QU4LITY
Project Team
Research Innovation