In the future, industrial systems should recognize their own faults and display suitable maintenance and troubleshooting information to technicians using mobile devices, data glasses or projections. Scientists at inIT are pursuing this vision together with industrial partners Kannegiesser and ISI Automation in the 'ADIMA' research project. The project name stands for "Adaptive assistance system for the maintenance of intelligent machines and systems (ADIMA)".

The aim of the project is to develop an assistance system that independently generates and visualizes maintenance information based on machine learning algorithms from decentrally recorded machine data. This should enable maintenance work to be carried out quickly and successfully by local technicians, even without machine-specific knowledge. "We want to realize simple maintenance and targeted fault diagnosis of systems with multimodal human-machine interfaces in order to enable less downtime and at the same time more working comfort for the technician through intelligent assistance systems," explains Professor Carsten Röcker, project manager and board member at inIT. For the Lemgo scientists, computer-aided assistance systems are the key to making the increasing complexity of systems manageable for people.

Demonstrator for SmartFactoryOWL

"The developments in the project are to be continuously tested for their practical suitability, which is why a demonstrator of the assistance system will be set up in conjunction with a real plant over the course of the project," explains Professor Oliver Niggemann, Director at inIT. "This demonstrator will be on display in the SmartFactoryOWL in the future, i.e. in a factory environment that shows future production in the context of Industry 4.0." Professor Jürgen Jasperneite, Institute Director of inIT, adds: "The assistance system we are aiming for is based on the Internet of Things (IoT), which we use to collect the data from very different sources of a machine and its environment in the necessary quality and process it for subsequent knowledge generation." According to Röcker, a reduction in the number of necessary service calls would allow plant manufacturers to concentrate on the profitable spare parts business in the maintenance sector. The Lemgo-based company hopes to see the first applications as early as 2019, with funding of around 600,000 euros from the German Federal Ministry of Education and Research (BMBF).