Introduction to Digital Twin Technologies
Course Title: SPTP: DIGITAL TWIN TECHNOLOGIES
CRN: 53268
Time: MW 3:00pm – 4:40pm
Location: ARCC 414
Credit Hours: 3
Spring 2025 (01/13/2025 – 05/06/2025)
Description
A digital twin is a virtual representation of real-world entities and processes, synchronized at a specified frequency and fidelity. The concept of digital twins can be traced back to the numerical simulation of physical systems, where theory/data-driven methodologies are adopted to make predictions and optimize physical systems. With the rapid development of sensing, communication, and computing technologies, digital twins have been developed and used to simulate real-world conditions with real-time data, improve operations, and enable optimizations at various scales.
This course will give a comprehensive introduction to digital twins and the technologies to make them possible. Specifically, the course will briefly introduce the tools and techniques for creating representation models and user interfaces for digital twins. It will also cover the basics of the Internet of Things, data science, and theory/data-driven modeling methods that make digital twins useful in practice. The project-based learning method will be adopted throughout this course. The course will be offered as a combination of lectures and lab sessions, providing an intensive and immersive learning environment. Students will work on challenging projects in groups, which engage them in solving problems and working in teams.
Prerequisites
Familiar with a programming language, such as Python or C++, and capable of finishing assignments with the language in other courses.
Learning Outcomes
Upon the completion of the course, in addition to mastering the concepts and methodology behind digital twins, students should be able to:
- Use the Unreal Engine and/or other technologies to create simple visual representations for digital twins,
- Apply machine learning and data analysis techniques to create data-driven models,
- Integrate the output from theory-driven models for real-time simulations,
- Use the Internet of Things (IoT) to collect and publish data, and
- Develop teamwork skills in a multidisciplinary environment.
Textbook and/or Resource Materials
All the materials will be provided.
Some useful links:
- Unreal Engine – https://www.unrealengine.com/en-US
- PyCharm – https://www.jetbrains.com/pycharm/
- Google Collaboratory – https://colab.research.google.com/
- MQTT – https://mqtt.org/
- ISO 23247-1:4, Automation systems and integration – Digital twin framework for manufacturing
Course Schedule
| Week | Topic | Project Timeline |
| 1 | Progress Report #1 | Select projects and form teams |
| 2 | Reference models of digital twins | Present initial concept |
| 3 | Visual representation of digital twins | |
| 4 | Design and development of UI/UX for digital twins | Digital twin development |
| 5 | Collecting and connecting data to the visual representation of a digital twin | Internet of Things (IoT) and information-sharing frameworks |
| 6 | Progress Report #2 | Testing |
| 7 | Midterm presentation of projects | Present project |
| 8 | Data management and analytics | |
| 9 | Data-driven modeling and machine learning for digital twins | Digital twin development |
| 10 | Real-time simulation for digital twins | Case studies with real-world digital twin applications |
| 11 | Digital thread | |
| 12 | Deployment of digital twin | Testing |
| 13 | Case studies with real world digital twin applications | |
| 14 | Final presentation of projects | Present project |
| 15 | Wrapup the course | Final report |