CF1 CyberFactory#1

Motivation

Increasing automation of factory plants through, for example, transport or assembly robots and networked machines promises increased efficiency in production. The networking of different factory components allows the entire system flow to be optimized instead of being limited to optimizing the behavior of individual components. New architectures, technologies and methods are needed for the development of such FoF, which not only increase the efficiency of the factory but also ensure the security properties of the FoF.

Goal

In the ITEA3 project CyberFactory#1, the Factory of the Future (FoF) will be enabled to continuously adapt to changing conditions and optimize itself, as well as to increase its resistance to physical and IT-technical threats.

The CyberFactory#1 project complements and expands other projects in the context of Industry 4.0 in terms of developing the following key capabilities:

  • The factory of the future is seen in CyberFactory#1 not only as a single plant or as a set of isolated plants, but as a network of interacting plants, as a System of Systems (SoS). The factory of the future, its environment as well as the people operating in the factory are to be captured in realistic digital models in order to be able to investigate simulation-supported design, test and validation of optimization and resilience components.
  • Methods will be developed that enable the FoF to automatically carry out continuous optimization of production. Real-time data about material, people and machines in the factory will be analyzed and the results will be used to optimize human-machine interaction and autonomous reconfiguration of production processes.
  • In addition, CyberFactory#1 develops methods to increase the resilience of the factory of the future. The project focuses on the development of methods for monitoring the behaviour of humans and machines for the automated detection of deviations, robust approaches for machine learning and mechanisms for assisted or autonomous reaction to detected anomalies.

These key capabilities are demonstrated in CyberFactory#1 in realistic use cases designed to reflect the diversity of possible new factories of the future (such as user-centric factories and learning factories). New business models such as the transition from product to service offerings and the development of data services to complement product manufacturing will also be considered.

Technologies

  • distributed simulation
  • Development and use of digital twins
Persons

Internal Leader

External Leader

Adrien Philippe Bécue (Airbus CyberSecurity SAS, France)

Scientific Director

Partners
Bluewrist Inc.
bluewrist.com
Bittium Wireless Ltd.
www.bittium.com
High Metal Oy
highmetal.fi
Houston Analytics Oy
houston-analytics.com
Netox Oy
netox.fi
Rugged Tooling
ruggedtooling.com
VTT Technical Research Centre of Finland Ltd.
www.vtt.fi
Airbus S.A.S.
www.airbus.com
Airbus CyberSecurity SAS
www.cassidian.com
LAAS CNRS - Laboratoire d'analyse et d'architecture des systèmes
www.laas.fr
Sigfox
Uwinloc
uwinloc.com
Airbus Cybersecurity GmbH
airbus.com
Aviawerks International GmbH
Brandenburgisches Institut für Gesellschaft und Sicherheit gGmbH (BIGS)
bigs-potsdam.org
Bombardier Transportation
rail.bombardier.com
Fraunhofer-Institut für Angewandte und Integrierte Sicherheit AISEC
www.aisec.fraunhofer.de
Hochschule für Technik und Wirtschaft Berlin
www.htw-berlin.de
InSystems Automation GmbH
www.insystems.de
IDEPA
idepa.com
isep Instituto Superior de Engenharia do Porto
www.isep.ipp.pt
SISTRADE Software Consulting, S.A.
sistrade.com
Airbus Defence and Space (Spain)
airbus.com
ENEO TECNOLOGÍA, S.L
carsa.es
Innovalia Association
www.innovalia.org
Nextel S.A.
nextel.es
PAL Robotics
pal-robotics.com
Trimek
trimek.com
GOHM Electronics and Computing Systems Ltd
gohm.com.tr
Lostar Information Security
lostar.com.tr
Accelerite
accelerite.com

Duration

Start: 01.06.2019
End: 31.05.2022

Founding Source