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regeNerAtive Resilient smaRt mAnufacTuring nEtworks

Project description

A closer look at the challenge and innovation of supply chain disruptions

Manufacturing and logistics companies grapple with frequent disruptions, leading to production slowdowns, increased costs and frustrated customer demand. These unforeseen events create a cascade effect, challenging the entire supply chain’s resilience. In this context, the EU-funded NARRATE project will develop the Intelligent Manufacturing Custodian (IMC). This tool provides end-to-end visibility and control over supply chain operations, predicting and mitigating potential disruptions. By integrating the IMC, supply chains evolve into smart manufacturing networks, capable of self-orchestration and resilience. A digital twin enhances IMC intelligence, enabling real-time monitoring and proactive decision-making. NARRATE aims to revolutionise supply chain management, enhancing productivity, sustainability and resilience across diverse industry sectors.

Objective

Manufacturing and logistics companies are subject to unforeseen events that disrupt the supply chain, causing production slowdowns, reduced output, and increased costs, making it difficult to meet customer demand. To mitigate these risks, manufacturers must build resilience across entire value chains.
NARRATE will develop a sophisticated tool using AI, Digital Twin, and IoT technologies allowing end-to-end visibility and control over supply chain operations to monitor and predict potential disruptions, enabling supply chains to achieve improved resilience.
The Intelligent Manufacturing Custodian (IMC) will leverage data from various production sources to enable proactive decision-making and act as a nerve centre for a supply-chain network, providing real-time monitoring and coordination of intelligent production processes and logistics. Integrating an IMC into a supply-chain will evolve its operations into Smart Manufacturing Network (SMN): a connected and self-orchestrated ecosystem linked end-to-end with programmable Manufacturing-as-a-Service capabilities that can withstand disruptions.
A Digital Twin will provide a reliable model to represent production and operational data of an SMN to unlock deeper IMC intelligence. Collected data will train machine learning models to predict potential disruptions, such as natural disasters or delayed shipments. AI algorithms will analyse the data and provide real-time reporting and visualization on a dashboard.
The IMC and Digital Twin interaction will generate powerful insights and self-adapting abilities that support an SMN to evolve under human supervision by switching services between multiple external partners to respond to risks and disruptions and improve energy efficiency, product circularity and environmental sustainability across the entire production process.
The effectiveness of NARRATE will be evaluated by testing the IMC in real production environments in quite diverse industry sectors.

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Keywords

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Topic(s)

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Funding Scheme

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-CL4-2023-TWIN-TRANSITION-01

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Coordinator

INSTITUTO TECNOLOGICO METALMECANICO, MUEBLE, MADERA, EMBALAJE Y AFINES-AIDIMME
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 665 937,50
Address
CALLE LEONARDO DA VINCI 38 PARQUE TECNOLOGICO
46980 Paterna Valencia
Spain

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Este Comunitat Valenciana Valencia/València
Activity type
Research Organisations
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 665 937,50

Participants (14)

Partners (1)

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