LineFLow is a python framework to simulate assembly lines. It allows to model
arbitrary discrete part assembly lines and provides an gymnasium environment to
optimize them with reinforcement learning. The documentation can be
found here.
Install with
pip install lineflow-rlThis is how an assembly line can be implemented and visualized:
from lineflow.simulation import Line, Source, Sink, Process
class SimpleLine(Line):
def build(self):
# Set up stationary objects
source = Source(
name='Source',
processing_time=5,
position=(100, 500),
unlimited_carriers=True,
)
process = Process('Process', processing_time=6, position=(350, 500))
sink = Sink('Sink', processing_time=3, position=(600, 500))
# Wire them with buffers
source.connect_to_output(station=process, capacity=3)
process.connect_to_output(station=sink, capacity=2)
line = SimpleLine()
line.run(simulation_end=500, visualize=True)
df = line.get_observations()This is how an RL agent can be trained using LineFlow:
from stable_baselines3 import PPO
from lineflow.simulation import LineSimulation
line = SimpleLine()
env = LineSimulation(line, simulation_end=100)
model = PPO("MlpPolicy", env)
model.learn(total_timesteps=100)Serve the docs with
mkdocs serveIf you use our work in your research, please consider citing us with
@misc{LineFlow,
title={LineFlow: A Framework to Learn Active Control of Production Lines},
author={Kai Müller and Martin Wenzel and Tobias Windisch},
year={2025},
eprint={2505.06744},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2505.06744},
}
See this README for more details how to run the benchmarks.
The research behind LineFlow is funded by the Bavarian state ministry of research. Learn more here.