The IoT Lab is part of the Center for Informatics Research (CIRT) at the University of Trier and provides necessary equipment to conduct research in the area of Internet of Things. The main parts are a soldering area and a Fischertechnik factory simulation model.

Fischertechnik Smart Factory

The used Fischertechnik factory simulation model consists of four modules: a sorting line with color detection, a multi-processing station with an oven and a milling machine, a high-bay warehouse, and a vacuum gripper robot. Each module is operated by its own controller based on an ARM Cortex A8 CPU with various analog and digital input/output ports running under a LINUX kernel. The model is equipped with nine light barriers and ten switches for control purposes of the actuators consisting of ten motors, three compressors, and eighth valves. For condition monitoring purposes, the model is enhanced with dedicated sensors such as four three-axis acceleration sensors that are mounted on motors and compressors and four differential pressure sensors measuring the pressure generated from the three compressors. Furthermore, two absolute orientation sensors, each with a gyroscope, an accelerometer, and a geomagnetic sensor are installed on the robotic vacuum gripper and the dispensing machine of the high-bay warehouse. Similar to the continuous transformation of a factory in the context of Industry 4.0, the model is in a continuous development phase so that in future more components such as RFID reader/writers as well as additional processing and transport units will be integrated.

For processing the data generated by sensors as well as process parameters (e.g., motor speed), the high throughput distributed messaging system Apache Kafka is used and Apache Cassandra is installed as database.

The simulation factory is used for research in the field of predictive maintenance and for implementing flexible production processes that adapt to changing requirements and unexpected situations (see EBLS4Industry project for more details). A video of the factory executing a manufacturing process and tracking of workpieces can be found here.

Current Projects

EBLS4Industry - Experience-Based Learning Systems for Industry 4.0 - Adaptive Production Processes and Predictive Maintenance

Publications & Download Data

Publications

A list of publications can be found here.

Download Data

As a result of our research, we have developed various software prototypes or resources, most of which are freely available and can be used for other research projects. The following list contains the download links to these. To use the resources, please read the corresponding paper or README file for more information for proper referencing:

• Dataset: IoT-Enriched Event Log for Process Mining in Smart Factories
  • Dataset Link: https://doi.org/10.6084/m9.figshare.20130794
    License: CC BY 4.0
     
• FTObjectDetection: Object Detection for Smart Factory Processes by Machine Learning
  • Video Link: https://doi.org/10.6084/m9.figshare.13240784
    License: CC BY 4.0
  • Implementation Link: https://gitlab.rlp.net/iot-lab-uni-trier/ft-object-detection
    License: GNU General Public License v3.0
  • Dataset Link: https://gitlab.rlp.net/iot-lab-uni-trier/ft-object-detection-dataset
    License: CC BY 4.0
     
• Smart Factory Control Code: The Smart Factory Control Code of the Fischertechnik factory used at the University of Trier
  • Resource Link: https://gitlab.rlp.net/iot-lab-uni-trier/smart-factory-control-code
    License: GNU General Public License v3.0
     
• FTOnto: A Domain Ontology for a Fischertechnik Simulation Production Factory by Reusing Existing Ontologies
  • Resource Link: https://gitlab.rlp.net/iot-lab-uni-trier/ftonto
    License: GNU General Public License v3.0
    
    Note: The domain ontology FTOnto also contains the semantic web services described in "Semantic Web Services for AI-Research with Physical Factory Simulation Models in Industry 4.0"