The project, which is part of the ITEA cluster of the European EUREKA programme, brings together 28 industrial and research partners from seven different countries- with the ultimate aim of enhancing the processes and the cyber-resilience of the Factories of the Future (FoF).
CyberFactory#1 (CF#1) aims to design, develop, integrate and demonstrate a set of key enabling capabilities to foster the optimisation and resilience of FoF.
Specifically, CF#1 will assist the development of key capabilities in the following areas:

Factory of the Future Modelling
  • Cyber-physical modelling and “digital twins”
  • Eco-system modelling, supporting real-time management decision-making
  • Human-behaviour modelling
  • Factory SoS modelling
Factory of the Future Optimisation
  • Real time sensing, tracking and supervision of tools, materials and individuals in the supply chain
  • Data-lake exploitation
  • Optimisation of human / machine collaboration
  • Distributed manufacturing capability
Factory of the Future Resilience
  • Authorisation, authentication and continuous trust level management
  • Resilient ArtificiaI Intelligence (AI) and adversarial machine learning
  • Human / machine watch and behaviour-based anomaly detection
  • Autonomous resilience and automated incident response capabilities

Our goals step by step

1. We are already supporting the use cases and misuse cases based on risk assessments

Use cases range from remote production monitoring, to supply chain optimisation or predictive maintenance, whereas misuse cases range from accidental malware insertion from an Advanced Persistent Threat (APT) or offensive AI ⇩

2. The modelling and simulation of cyber-physical systems which will populate the FoF

They will utilise architecture validation, data generation, equipment testing and user training to support the adoption of smart secure manufacturing technologies

3. Focus on capabilities that enhance the resilience and security of the FoF

Particularly through resilient AI development (CAP52), human/machine behaviour monitoring (CAP53) and autonomous cyber-resilience mechanisms (CAP54)

4. These developments will be integrated and tested in pilot factories with application sectors ranging from aerospace to robotics or electronics

A total of 8 pilot factories will be involved in the demonstration of project results with the deployment of modular system demonstrators, integrating developments of the whole consortium

Factory of the Future characterisitics

Multifunctional production system


    The FoF should be able to deal with short production cycles efficiently, constantly changing production contents and strong customisation. It should also be able to respond flexibly and adequately to deviations and disturbances


    The FoF by nature is flexible and system associations are constantly adapting to changed boundary conditions and goals. This means that deviations from normal or desired behaviour and hazards are much more difficult to detect than in traditional manufacturing systems
People and machines collaboration


    To benefit from the augmentation of human and artificial intelligence, the cooperation of people with robots and other automats without explicit spatial separation must be enabled.
Big Data


    In the FoF, very large amounts of data are collected cumulatively. The challenge is to analyse this huge amount of data in real time, in order to recognise patterns and make decisions, based on data output.
Artificial Intelligence


    The FoF will use AI methods for monitoring and anomaly detection, decision support or automated control, self-optimisation and autonomic resilience.