This repository contains the Microservices-based Python-based software system to control smart factory training models with hardware provided by Fischertechnik. The control of the hardware relies on the fischertechnik TXT controllers acting as PLCs.
A scientific publication describing the internals of the software stack can be found here:
Seiger, R., Malburg, L., Weber, B., & Bergmann, R. (2022). Integrating process management and event processing in smart factories: A systems architecture and use cases. Journal of Manufacturing systems, 63, 575-592.
To use this software, the TXT controllers of the factory need to be running the fischertechnik TXT community firmware. The controllers need to be connected to the same IP-based network, either via Wifi or Ethernet.
The computer running this Python project has to be connected to the same network and it needs to be able to talk to all controllers via TCP.
The IP addresses of the TXT controllers follow the scheme: 192.168.0.xx with xx being passed as argument to the constructors of the classes representing an individual station in the txts folder (e.g., HBW1.py, MM1.py). Below you can find a picture with a sample configuration of controllers and their IP addresses.
External libraries used in the project are specified in the requirements.txt file. They can be installed for each microservice via pip.
All TXT controllers need to be up and running the fischertechnik community firmware, have an active network connection, and run the FTGui app. To start the entire system, you have to run the Docker compose file provided in the root folder via a terminal:
docker compose upThis starts all the microservices for the individual production stations, as well as an instance of Apache Kafka and Camunda 7 Platform.