Digital Twins for Digital Manufacturing

This program focuses on creating advanced technologies to develop Digital Twins for key manufacturing entities like machines, personnel, products, and processes. These Digital Twins will improve production efficiency, ensure product quality, reduce maintenance costs, and enhance sustainability.

Aims:

  • Develop novel technologies to model industrial machines, personnel, products, and processes.

  • Create techniques for linking physical entities with their digital counterparts through Digital Twins.

  • Establish a framework for managing the lifecycle of Digital Twins for continuous improvement.

Outcome:

  • This program will reduce the cost and effort of creating Digital Twins by minimising the need for extensive individual programming and decreasing the overall number of Digital Twins required, thereby streamlining processes and enhancing efficiency for our partners.

Projects

Title: AI Models for Digital Manufacturing

Summary: This project will develop AI/ML models and an open platform to enhance digital manufacturing,

addressing predictive maintenance, product quality, and production efficiency. The AI/ML models will

proactively predict, prevent, and fix issues using Digital Twins, while the platform will provide a flexible

framework for model integration, runtime management, and edge computing for seamless

deployment across various manufacturing environments. Outcomes include autonomous diagnostics,

improved product consistency, optimised production planning, and a resilient, scalable edge system

for real-time manufacturing support.

Team

Project Leader: Prof. Yang Xiang

Project Industry Parner Investigator: Lin He

Project Personnel: Prof. Dimitrios Georgakopoulos, Dr. Wei Zhou, Dr Wanlun Ma, Dr Sheng Wen,