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AI4DI – Artificial Intelligence for Digitising Industry

Project Description

In the era of digital transformation, when flexibility and deep understanding in manufacturing of complex products becomes the key competitive advantage, Artificial Intelligence (AI) is the accepted method to drive the digitalization for the transformation of the industry and its products.

However, the potential of AI in economy and society is by far not enough exploited. The users of AI are not sufficiently supported to facilitate the integration of AI into their applications. Enabling of performance, industry and citizens by AI for digitising industry is the key to push the AI revolution in Europe and step into the digital age.

Existing services providing state-of-the-art Machine Learning (ML) and artificial intelligence solutions are currently available in the cloud. The project will transfer machine learning and AI from the cloud to the edge in manufacturing, mobility and robotics applications. To achieve these target, factories, processes, and devices within digitised industry will be connected by utilizing ML and AI for human machine collaboration and change and anomalies detection. Hence, more knowledge will be extracted from the existing data by arranging them into a processable representation. This knowledge will change the semantics and the logical layer with a distributed system intelligence for e.g. quality control, production optimization.

AI4DI’s high level objectives are:

  • Accelerate the AI adaptation to serve European priorities in the digitizing of the Industry.
  • Maximize the benefits of Moore’s Law and More Moore and revive Moore’s Law beyond the current technology.
  • Build a European AI community with European values.

The project will deliver several solutions including different AI-based functions and will be validated in 15 industrial demonstrators such as:

  • An application for analysis, planning and decision-making powered by AI-based methods for the complex logistics control processes, such as supply chain control strategy and distributed and secure computing with data anomaly checks.
  • An innovative edge-based system with integrated Machine Learning (ML) algorithms for 3D image analysis, trends recognition and full supervision availability for improved product quality.
  • An automated wood machinery with Augmented reality (AR), Voice recognition and direct operator interaction to enhance safety and productivity on autonomous and collaborative robots and machine tools in their interaction with human operators.

AI4DI consortium is composed of 40 highly experienced partners along the entire value chain, OEM, Tier 1 and Tier 2 suppliers, semiconductor industries, research institutions and academia.

AI4DI receives funding from the European H2020 Research and Innovation Programme, ECSEL Joint Undertaking (grant agreement no 826060) and from the Austrian Ministry for Transport, Innovation and Technology under the funding programme “IKT der Zukunft” (Austrian national funding for ECSEL, grant agreement no 871642).


TTTech Industrial Automation together with TTTech will develop a fog computing platform for seamless deployment and execution of AI-based functions and considering industrial requirements such as latency and processing power. TTTech will contribute to the platform validation in an AI supported automotive manufacturing and logistics use case.


Francesca Flamigni

Edin Arnautovic

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