Scope and Objectives

To develop a new generation of AI models (semi-automated knowledge discovery) and data management tools, and combine them with other technologies, tools and services (digital twin, DSS, etc.), in order to support humans to make decisions, collaborate better with AI systems, and fuse (human-AI) knowledge. The project’s main aim is to boost industries towards agile and flexible strategies, able to respond to the fast-changing customers’ needs, and in the same time to optimise their processes and quality control mechanisms.

knowlEdge targeted Breakthrough
knowlEdge Innovation Response

AI offers huge advantages over traditional automation. According to Accenture, AI could double the annual economic growth rates by 2035 and create new relationships between people and machines, keeping people in control. Efficient big data analytics and AI models generated for manufacturing IoT could improve:

  •   The factory operations and production
  •   Reduce machine downtime
  •   Improve product quality
  •   Enhance supply chain efficiency
  •   Increase resource and energy efficiency
  •   Warrant safety and risk management
  •   Orchestrate the pathway to a carbon- neutral economy, and
  •   Improve the customer experience

Furthermore, an increase in responsiveness within supply network is envisioned if explainable AI simulations, visualisations, notifications, etc., are provided to decision-makers. The capability of AI techniques and technologies is further enhanced when they are distributed in the compute continuum e.g. Cloud technologies provide the opportunity to scale rapidly with lower computing costs, on the other hand, computation at the edge and on the fog drastically improves accuracy, response time and security. Moreover, AI with human-in-the-loop allows further increase in flexibility, agility and competitiveness. This also support skill development and increased competitiveness. The use of transparent and explainable AI solutions allows humans to be trained and development of their skills through knowledge capturing mechanisms. The human-AI collaboration is expected to play an essential role towards knowledge generation and decision making.