/thesisdigitaltwinsustainability

Software components used for my Thesis about Digital Twin and sustainability in manufacturing

Primary LanguageGoGNU General Public License v3.0GPL-3.0

Thesis Digital Twin and sustainability in manufacturing

Welcome! This repo describes the installation and configuration of the sustainable digital twin used for my thesis. When my research paper is finished, it will be also shared here. Please contact me if you have any questions!

All the steps that I have taken are noted here in my logbook.
A full video of the experiment can be watched here

High Level Architecture

Below you can see the high level architecture of the sustainable digital twin

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1. Machines in the productionline - are simulators of machine data
2. Azure IoT Central is used to receive the raw machine data
3. Azure Data Explorer is used for long term storage and machine learning (forecast energy and anomaly)
4. Azure Digital Twins for latest data points of machine and placing it in the context of the production line
5. Azure Functions sends data from Azure IoT Central to Azure Digital Twins
6. Azure Digital Twins 3D scenes is used to create the 3D view of the sustainable digital twin
7. OEEE dashboard is created on Azure Data Explorer to calculate the OEEE and showcase the forecasts of energy and problems in the production line

Installation of base infrastructuur

On the following page you can find the installation of the Azure components used in the sustainable digital twin https://github.com/rploeg/thesisdigitaltwinsustainability/blob/main/documentation/install.md

Configuration Digital Twin

On the following page you can find the configuration of the Digital Twin that represent sustainable digital twin
https://github.com/rploeg/thesisdigitaltwinsustainability/blob/main/documentation/configdigitaltwin.md

Configuration of Simulator

On the following page you can find the configuration of the simulator that send simulated data to the sustainable digital twin
https://github.com/rploeg/thesisdigitaltwinsustainability/blob/main/documentation/datapoint.md

Use Machine Learning components

In the research also two algorithms are used.
https://github.com/rploeg/thesisdigitaltwinsustainability/blob/main/documentation/ml.md

Result

If everything is configured correctly you should have two dahsboard:

  1. OEEE dashboard with extra E for energy included together with forecasting and anomaly
    image

2. 3D view of the sustainable Digital Twin based on one foodpackaging production line

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Used libraries

The following libraries are used to build up the DTDL tree in Azure Digital Twin. Because placing comments is not allowed in the DTDL structure the credits are placed here. Also the other libraries that are used are here:
DTDL: https://github.com/Azure-Samples/digital-twins-samples/tree/master/HandsOnLab
OEE: https://github.com/Azure/iot-central-industrial-OEE - used for simulator and baseline for machine template

I want to thank these authors for their work!