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BA_data

Code and Data regarding my Bachelor Thesis with the title "Local management of historic production data of a 3D-Printer"

A local data storage for a 3D printer is build based on the data lake concept. It uses octopi for the data access of the 3D-printer, a python script capture the camera frames, minio as data storage and node-red to create the data pipelines and Interfaces.

Node-RED and minio are combined into a docker compose setup, because those two components are most likely to get reused in other implementations. Also they do not need access to the usb-ports as the other two components, which can be tricky using docker. For node-red it uses the base image with some npm packages pre-installed as well as my fork https://github.com/ReggaeUlli/node-red-contrib-minio-all of the node-red-contrib-minio-all package which fixes a bug regarding missing metadata after put commands. Also the original input messages are now passesed with the new payload to the output, which enables better message tracing and more complex flows.

This repository consists of following elements:

  • directory "docker" contains the docker files to start node red and minio
  • file "stream.py" which contains the python camera script
  • file "exampleFlow.json" which contains the node-red flows for the given example application
  • diretory "Benchmark tests" contains the gcode files and pictures of the results regarding the benchmark tests.

The "exampleFlow"-File contains following flows:

  • "emulated Printer" which emulates printer data for test purposes
  • "printer AAS" which combines the data from octopi and the camera and communicates with the datalake
  • "datalake AAS" which handles the incoming data and puts it into the data lake
  • "transformations" which handles the transformations done inside the data lake
  • "dashboard" which creates the dashboard

In theory only flow "printer AAS" needs to be modified to use this implementation for other applications

Install

Install octopi

install the octopi image on an SD following the offical guide: https://octoprint.org/download/

install minio and node-red

on a arm system with linux operating system (for example the octopi image mentioned above):

install docker

curl -fsSL https://get.docker.com -o get-docker.sh
‍Sudo sh get-docker.sh
sudo apt-get install libffi-dev libssl-dev
sudo apt install python3-dev
sudo apt-get install -y python3 python3-pip
sudo pip3 install docker-compose

create the docker volumes for persistent data

docker volume create minio_data
docker volume create node-red_data

Download this repo:

wget https://github.com/ReggaeUlli/historic_production_data/archive/refs/heads/main.zip

unzip

unzip main.zip

change directory

cd historic_production_data-main/docker

start

docker-compose up

access node red via

<ip of host>:1880

access minio via

<ip of host>:9000

laod example flows from the flows.json file and fit for your usecase

install the python script for camera pictures:

install python

apt-get install python

install pip

apt-get install pip

install socket package

pip install socket

install OpenCV

pip install pip opencv-contrib-python

run the camera stream script by navigating to the directory of the repo and running

sudo service webcamd stop
python camera_stream.py

Notice:

  • you may need to run the docker and apt-get commands as sudo
  • after changing the nodered docker file you may need to run the following once before starting the containers again in order to rebuild them:
docker-compose build
  • if installing opencv on the pi leads to problems follow: https://raspberrypi-guide.github.io/programming/install-opencv
  • For both the node-red as well as the minio application external volumes needed. This requires an extra step of creating these volumes before useage, but provides better data persistency. A normal named volume would be automatically created by "docker-compose up" but would also be deleted by "docker-compose down". In this case only "start" and "stop" commands musst be used. If this is desired it can be achieved by deleting the "external" tags in the "docker-compose.yml" file
  • the flows.json musst be manually imported into node-red once. This is because copying by using the docker file is not possible. After building the image the file would get overwritten when mounting the volume. A wourkaround would be something like a skript which adds the flows.json to the volume.