Digital Twins and Industrial Simulation

Overview

Delivered by the Media Lab in partnership with NVIDIA and the Advanced Manufacturing Innovation Centre (AMIC), this module provides a hands-on introduction to the creation and operation of digital twins within an industrial context.

Students will engage with a pre-populated industrial environment, designed to simulate processes, production lines and human interactions in connected systems and settings.

Through guided tutorials and applied experimentation, students will learn how to visualise, optimise, and automate industrial processes in a physically accurate virtual environment. Participants can choose to:

Modify the existing setup through process simulation, asset manipulation, or system automation.

Integrate external data or design systems using (e.g. Autodesk, Unreal, SolidWorks, or Python-based IoT interfaces).

Extend the simulation through AI-driven behaviours, robotics control , or data visualisation dashboards.


Students will attend a series of six tutorials introducing simulation engine fundamentals, scene management, physics-based simulation, collaboration workflows, and real-time rendering.

An AMIC guest lecture will demonstrate real-world industrial digital twin applications, linking the academic work to current manufacturing innovation practice.

The module culminates in an assessed project, where students working in groups collaboratively develop and present their enhanced digital twin environment.

Learning Objectives

By the end of this module students will be able to:

- Demonstrate knowledge of the principles and workflows underpinning digital twin development..

- Apply physics, programmable events, AI, and rendering techniques to model real-world processes.

- Communicate their design and technical decisions effectively through visual, written, and oral means.

Skills

By the end of this module students will be able to:  

Employ a real time simulation engine for real-time collaborative design and simulation.

Apply iterative problem-solving and design thinking to digital twin development.

Demonstrate professional competency in project planning and self-directed learning.

Translate industrial systems into virtual models for testing and evaluation.

Present technical and creative work effectively to academic and industry audiences.

Assessment

Assessment in line with learning outcomes



The emphasis is on applied understanding of simulation workflows, technical implementation, design rationale, and reflective analysis of performance or efficiency outcomes.



Formative feedback will be provided throughout, with one formal mid-point review and a final presentation session before an internal panel. An individual project report will accompany the submission, outlining design intent, reflection on each students contribution to the project, integration methods, and evaluation.