Imagine your factory is like a Lego set that can be rebuilt instantly when a piece goes missing or a supplier disappears. This system uses a digital twin—a virtual mirror of the factory—to predict disasters and automatically find new ways to keep production running. It's like having a GPS for your supply chain that reroutes you around traffic jams before you even hit them.
Manufacturers struggle to maintain production when unexpected events like pandemics or material shortages disrupt their supply chains. Current systems lack the agility to quickly reconfigure production networks to avoid costly downtime.
A trusted Manufacturing-as-a-Service (MaaS) platform featuring a resilience predictor, hybrid twins for the Industrial Metaverse, and a scoreboard analyzer app.
If you are a component supplier dealing with raw material shortages—this project developed a trusted network platform that allows you to switch production to other available services. This can lead to a process ramp-up time improvement of over 26%.
If you are a manufacturer dealing with unexpected border closures—this project developed a resilience predictor and scoreboard app that optimizes the network. This aims to reduce product costs by more than 9%.
If you are an OEM dealing with volatile demand—this project developed hybrid twins and Industrial Metaverse interfaces to simulate better scenarios. This can increase Overall Equipment Effectiveness (OEE) by more than 14%.
Based on available project data, the system targets a product cost reduction of over 9% and a cost per piece reduction of over 38%.
Yes, the project is designed for industrial manufacturing value networks and involves 10 industry partners to ensure practical application.
Based on available project data, the platform uses smart service-level agreements and contracts to ensure reliable and trusted data sharing within the network.
The project targets a process ramp-up time improvement of more than 26%.
It integrates through multi-source sensing of supply chain disruptions and the use of Hybrid Twins that connect physical equipment to a digital metaverse.
The consortium is heavily weighted toward commercial application, with 18 partners including 10 industry players (56% industry ratio). The dominance of SMEs (13 out of 18) suggests the technology is being built for agile, mid-market manufacturing environments rather than just academic research.
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