Project Cyberfactory#1: Cybersecurity & fleet cobots in Factories of the Future


PAL Robotics at Cyberfactory No. 1

How can we develop and optimise Factories of the Future for success? This is what EU project Cyberfactory No.1 aims to address, as it has embraced the technical, economic, human and societal aspects of Factories of the Future. Over recent years, the project has worked with over 25 partners from seven countries (Canada, Finland, France, Germany, Portugal, Spain, and Turkey), including PAL Robotics. Our robots, the autonomous mobile robot TIAGo Base and mobile-manipulator TIAGo take part in the project.

The project has included a number of high-profile pilots with industrial project partners, and cybersecurity, fleet cobots, and digital twins are just some of the areas that have been covered. Partners include pilot users, research organisations, and suppliers. During the project, pilots have been carried out in Transportation, Automotive, Electronics, and Machine manufacturing industries. 

CyberFactory#1 has the aims of:

  • Designing, developing, integrating, and demonstrating a set of capabilities to promote optimization and resilience of the Factories of the Future (FoF)
  • Proposing preventive and reactive capabilities to address security and safety concerns.

At PAL Robotics we have taken part in various use cases for Cyberfactory No.1. Here are all of the project use cases in more detail, which aim to improve manufacturing processes, security, and collaboration between humans and robots. 

Discover how TIAGo works for the Factory of the Future.

Project use cases including in the aerospace industry, automotive industry, textile production and cheese manufacturing

High Metal

In this use case a highly automated food production line is being developed (for cheese making). The High Metal use case introduces a new integrated platform-based concept for cheese manufacturing that enables better flexibility for product quality changes, scalability for production increases, shorter installation as well as production start-up time and better efficiency and easier maintenance compared to traditional dairy production lines.


The IDEPA use case is digitalizing a textile production line (legacy machines) for the automotive industry. The goal is to increase efficiency as well as security, safety and resilience, focusing on the development of a new generation of ERP tools, considering Security Awareness and providing Data & Knowledge as a service. 


The Bittium use case looks at a cyber-secure networked supply chain and information architecture. The goal is to create a consistent and secure information architecture and develop processes as well as information tools, which are able to support digital partnered manufacturing and deliveries, to achieve supply chain optimization.

Airbus Defence & Space (Spain)

At Airbus use cases are defined for the deployment of Industrial Internet of Things (IIoT) for management and optimization of manufacturing and assembly lines in the Aerospace Industry. This includes:

  • Roboshave (Tablada Site): Connectivity of the Roboshave station to the IIoT to improve traceability, supervision and maintenance of the processes.
  • Autoclave (CBC Site): Real-time monitoring and quality process automation across the IIoT within the Autoclaves area.
  • Gap Gun (San Pablo Sur Site): Automation of the data acquisition using a Gap Gun device (smart tool for gaps and steps measuring) with a centralized data storage.


This use case covers optimization of material handling in PCB assembly lines. The objective is to pass from conventional material handling managed by operators and without data gathered from machines, to move towards the integration of machines in the electronic board assembly line with ERP systems, warehouse and carrier robots in order to achieve optimization of production and improving traceability, as well as considering cybersecurity.

Bombardier Transportation

The Bombardier Transportation use case is optimising the material supply for rail vehicle production. The main objective is the optimization of material supply for railway vehicle production by building an automatic supply system from the warehouse directly to the workstations, to have a safe and automated provision of the material within its various physical levels.

ASTI Mobile Robotics

This use case addresses the optimization of an autonomous transport robot fleet (ProANT) and is focused on the collection of data from normal operations of a transport robot fleet that can be used for detecting individual patterns via ML and predictive systems. This information can be also used for logistics optimization for adaptation to continuous changes.


This use case addresses Human/Machine collaboration in manufacturing for quality control.

In detail it looks at the evolution of solutions, through integration with fully automated processes within the automotive industry. This means an overall enhancement of the Metrolab Scenario (incorporation of several cybersecurity tools/services, including cobots). PAL Robotics’ TIAGo Base, our AMR for indoor deliveries, takes part in this use case. TIAGo, our mobile manipulator suitable for research in HRI, manipulation, navigation and perception is also part of this use case.

Characteristics of Factories of the Future including short production cycles and collaboration between humans and robots

Cyberfactory#1 lists the following as characteristics for Factories of the Future: 

  • As a multifunctional production system, the FoF should be able to deal efficiently with short production cycles and constantly changing production. It should also be able to respond flexibly and adequately to deviations.


  • The FoF is by nature flexible and system association constantly adapting to changing boundary conditions. This means as well that deviations from normal or desired behaviour and hazards are much more difficult to detect.


  • In the FoF human and machines work in close collaboration. Increased automation in the FoF leads to a strong increase in the direct cooperation of humans with robots and other automated facilities without explicit spatial separation.


  • In the FoF, very large amounts of data are collected cumulatively. The challenge is to analyze this huge amount of data in real-time, recognize patterns and draw conclusions.


  • The FoF will use AI-based methods for monitoring and anomaly detection, decision support or decision automation, and behavioral optimization in a variety of areas.

Cyberfactory#1 partner events in Barcelona and Paris to discuss use cases

With the project soon reaching its end date, various events and meetings for project partners have been held recently across Europe. At the Consortium meeting on the 21st and 22nd September the team at PAL Robotics hosted multiple project partners. Partners had the chance to meet at our offices in Barcelona and discuss the project use cases and how these are making an impact. 

On the 27th of October the project held the ESM2021 event in Rome for all project partners, with keynote speeches and paper sessions from AirBus, ISEP – Instituto Superior de Engenharia do Porto, VTT Finland, PAL Robotics and OFFIS.

Most recently, the test review meeting took place in Paris on the 9th of December. The group discussed the demonstration of use cases by partners including Airbus, Bittium, High Metal, IDEPA, Vestel, Alstom, S21Sec, and ASTI. At PAL Robotics we presented our work on simulated cobot AMR and anomaly detection interface in ROS.

As the project nears its end, project partners are planning national workshops to present the findings of the project as well as a final demonstration of all use-cases at events in spring and early summer 2022.

Find out more about project Cyberfactory#1 and the work on this collaborative project by visiting collaborative projects on our website. If You would like to talk more about collaborative projects and ways to work together, do not hesitate to get in touch with us. To learn about the capabilities of our mobile-manipulator, TIAGo and AMR, TIAGo Base take a look at our blog posts! 

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