Scortex - Technology partner of COGNITWIN
Scortex - Technology partner of COGNITWIN

Scortex - Technology partner of COGNITWIN
Published on
Dec 4, 2019
by
Scortex team
We are proud to announce that Scortex is a technology partner of the consortium created for COGNITWIN (Cognitive Digital Twin). The Consortium aims to add cognitive elements to existing process control systems, allowing them to self-organize and provide solutions to unpredictable behaviors.
As part of this system, Scortex will bring its hardware expertise to implement deep learning algorithms on the robust and reliable FPGA platform (Field-Programmable Gate Array), enabling powerful real-time computing at the heart of the factory.
Cognitwin aims to define a new standard for the design, development, and operation of European industrial manufacturing processes by introducing a platform for virtual architecture based on components. It integrates IoT, Big Data, AI, smart sensors, machine learning, and communication technologies, all connected to a new paradigm of self-learning hybrid models with proactive cognitive capabilities. One aspect of the vision is the cognitive element, where processing factories can learn from historical data and adapt to environmental changes while being able to predict undesirable events in operations before they occur.
To achieve the project's objectives, Cognitwin has assembled a consortium of six process industries, four research groups, and four technology partners from seven countries, each bringing its expertise in data analysis and pattern recognition that will be at the heart of the COGNITWIN solution platform.
This European partnership aligns with the trajectory outlined in our seed funding announcement, which highlights our commitment to accelerating industrial innovation.
The project, funded under the EU's Horizon 2020 SPIRE Program, has an estimated duration of 36 months and is expected to start in the last quarter of 2019. Its total budget amounts to 8.6 million euros, including an EU contribution of approximately 7 million euros.
Scortex - Technology partner of COGNITWIN

Scortex - Technology partner of COGNITWIN
Published on
Dec 4, 2019
by
Scortex team
We are proud to announce that Scortex is a technology partner of the consortium created for COGNITWIN (Cognitive Digital Twin). The Consortium aims to add cognitive elements to existing process control systems, allowing them to self-organize and provide solutions to unpredictable behaviors.
As part of this system, Scortex will bring its hardware expertise to implement deep learning algorithms on the robust and reliable FPGA platform (Field-Programmable Gate Array), enabling powerful real-time computing at the heart of the factory.
Cognitwin aims to define a new standard for the design, development, and operation of European industrial manufacturing processes by introducing a platform for virtual architecture based on components. It integrates IoT, Big Data, AI, smart sensors, machine learning, and communication technologies, all connected to a new paradigm of self-learning hybrid models with proactive cognitive capabilities. One aspect of the vision is the cognitive element, where processing factories can learn from historical data and adapt to environmental changes while being able to predict undesirable events in operations before they occur.
To achieve the project's objectives, Cognitwin has assembled a consortium of six process industries, four research groups, and four technology partners from seven countries, each bringing its expertise in data analysis and pattern recognition that will be at the heart of the COGNITWIN solution platform.
This European partnership aligns with the trajectory outlined in our seed funding announcement, which highlights our commitment to accelerating industrial innovation.
The project, funded under the EU's Horizon 2020 SPIRE Program, has an estimated duration of 36 months and is expected to start in the last quarter of 2019. Its total budget amounts to 8.6 million euros, including an EU contribution of approximately 7 million euros.

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