Ambitions for I4.0 Lab

SDU's ambitions with I4.0 Lab:

  • To strengthen and develop the ecosystem around Industry 4.0 through collaborations and partnerships between scientists, students and companies
  • To strengthen funding for the area, considering that Denmark invests significantly less in innovation in production than other comparable nations
  • To create awareness of Industry 4.0 through demonstration centres with affiliated task forces
  • To educate the workforce with new competences with a focus on educating robotics engineers and strengthening basic technical understanding.

Once the lab is fully operational, numerous production cells will lay the foundation for a vibrant laboratory where scientists and students work closely together with representatives from production companies and robot companies to develop the most effective production environment. 
The lab will allow students and scientists to work with projects on all levels and test theories in realistic settings with real-life challenges and issues. Robotics companies can have their collaborative robot components tested and refined in an authentic factory environment, while production companies will be able to receive ideas from students and scientists on how they can develop their production by incorporating new technology to save time and money.  


Industry 4.0 creates a line of technological drivers which can realise the ecosystem:

  • Advanced and new technologies within robotics can take over both manual processes and collaboration with humans and other robots in the processes 
  • Horizontal and vertical integration of the entire supply chain through software solutions so that a coherent value chain from the manufacturer to the consumer can be created on top of a fully automated production 
  • Industrial Internet of Things covers both the hardware side with sensors and embedded electronics, and the corresponding decentralizing software part with local processing and network service
  • Augmented and virtual reality provide new opportunities to work with digital representations in the design phase, both for products and product systems. Simultaneously, the new interaction forms support the staff with the system since computer-created information can be superimposed on top of a picture one is looking at, e.g. through glasses or on an iPad
  • Simulation and emulation give opportunity to test and optimize based on virtual models, both in real time and prospectively 
  • Data science covers big data analyses for optimisation of product systems and artificial intelligence, which supports local decision-making competences and adaptability
  • Cyber security will be one of the main challenges in future systems because they are open, network-connected systems, which makes them vulnerable to hacking  
  • Cloud services allow constant online access to production data and dynamic updates in the system, including handling huge amounts of data with fewer requirements for local processing in the production elements

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