The Challenge

The LIAA Project was initiated to find a technological solution such as virtual training to keep assembly jobs, the most labor intensive part of manufacturing, in Europe. Small batch sizes, large number of variants, a significant number of parts and processes, and limited opportunities for automation make the assembly process labor intensive and costly. As a result, the assembly process, which is the last step in the manufacturing process, is often outsourced to lower wage countries such as China and India. By applying innovative technical solutions, the LIAA Project is looking for ways that boost efficiency while maintaining the flexibility needed for small or customized setups.

LIAA received a grant from the European Union’s Seventh Framework Programme for research, technological development and demonstration for 8M Euros.

High Cost of Automation

Large scale automation yields tremendous efficiency when there is a highly repeatable process. The costs of implementing robotics and other technology for automation is then spread out over large batch sizes with long production runs. With smaller more custom assembly work, these large automation costs are not carried by large volumes of product and do not have the flexibility to meet the demands of smaller specialized assembly tasks.

Flexible Manufacturing Needed

Automatic and Hybrid (combining robotic and human stations) manufacturing systems have difficulty handling the on demand nature of modern manufacturing. These systems cannot be adapted on a daily basis for fluctuating order volumes and production requirements.

The Solution: Virtual Training

As part of the LIAA Project, EON Reality together with OPEL and University of Patras developed an advanced man-machine interface allowed a human factory worker to assemble an turbocharger in concert with a robotic arm. The human worker received virtual training instructions through a Hololens and controlled the robotic arm with a smart watch. Together the human and robotic arm were able to be more efficient with the human performing the custom tasks as prompted by the AR display and the robotic arm handling the repeatable tasks. The tasks were performed on an turbocharger assembly by OPEL which required a reasonable level of dexterity but also character recognition and part assembly.


While the assembly tasks could reasonably be performed by a person and rank as “ergonomically feasible” activities, they can cause strain and long-term damage to the human body. With automation, the robotic arm takes on the lifting of the 5kg (11lbs.) part while the human bolts it into place. This restructuring of the task results in substantially less repeatable stress.


The assembly automation has to deal with different variants of the OPEL turbocharger and has to accommodate different geometries of the product variants. The robotic arm performs the highly repeatable portions of the procedure and eases the strain on the human operator while leaving enough flexibility for the operator to handle the highly variable portions of the assembly.

The Results

EON Reality presented this work together with its partners at several conferences/exhibitions:

  • Automatica 2016, Munich, Germany
  • Motek 2016, Stuttgart, Germany
  • European Robotics Forum, 2017, Edinburgh, Scotland
  • European Robotics Forum, 2014, Rovereto, Italy