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Digital Production

AI-powered production calls for an ever-growing convergence of the digital and physical systems of a smart factory. Reboot IoT Factory proposes a holistic and hierarchically organized perspective to this connected, data-driven factory. Our vision is that data flows fluently across networked digital twins, enabling new data-driven innovations in production as well as in products and related added value services.

We research data sharing and governance models to lay a groundwork for new value creation. Networked digital twins of production equipment and manufactured products enable the use of advanced analytics such as artificial intelligence and machine learning for different levels of adaptation, optimization, autonomy and efficiency. Situation awareness is increased through real-time visualizations of processes. Real-time data-driven simulation and prediction models offer agility in auto-configuration, self-scheduling and optimization of processes. Within the smart factory, historical and real-time data is used to identify anomalies and to prevent quality and safety issues. Reboot IoT Factory tackles these challenges of AI-powered production through a series of co-created proof-of-concepts.

"Reboot consortium has supported us in developing and implementing new innovative IoT 4.0 solutions into factory daily operations and thus helping moving forward in our digital Conscious Factory transformation journey." Mika Kaivola, Nokia

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"Before Reboot IoT Factory we were mostly exporting our AR technologies. This project gave us a chance to enter also the big Finnish manufacturing companies allowing us to be even more innovative and quicker in deployment of novel solutions in a growing market segment." Peter Antoniac, Augumenta CTO

Digital production focus areas

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How do I get involved?

In order to get involved in our grand challenge of digital production,  please contact us either directly or using our Fenix business case management tool. We are glad to tell you all about the available business opportunities.

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