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Project

European Data as a PRoduct Value Ecosystems for Resilient Factory 4.0 Product and ProDuction ContinuitY and Sustainability (RE4DY)

As part of the green, circular and digital transformation of the European manufacturing community, it is extremely important that data-driven digital manufacturing processes urgently incorporate innovative and active resiliency strategies at production and supply chain levels to maintain their sovereignty and competitiveness levels, respecting European digital values (excellence, privacy, trust) to improve individual and value chain flexibility. In order to achieve long-term resilience to reorganise supply chains or speed up decision making to dealt with any disruption, it is imperative to ensure the implementation of distributed data-intensive intelligent and dynamic industrial decision support, augmentation and automation processes, integrating Artificial Intelligence (smart anticipation) and Intelligent Automation (rapid response) capabilities in Human-Automation symbiosis. Hence, only businesses that can articulate their data, based on AI, digital thread and digital twin solutions, will be able to react rapidly to external shocks.

RE4DY mission is to demonstrate 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, proposing Data as a Product core concept to facilitate the implementation of digital continuity across digital threads, data spaces, digital twin workflows and AI/ML/Data pipelines. This concept leverages resiliency on top of advanced manufacturing digital processes and value ecosystems supporting the development and implementation of digital continuity, so distributed data management solutions implemented to deal with factory resiliency can be immediately and seamlessly reused to enhance connected factory and value network level processes.

Date:1 Jun 2022 →  Today
Keywords:data-driven digital manufacturing processes, Artificial Intelligence, Intelligent Automation, Human-Automation symbiosis
Disciplines:Manufacturing automation