Digital Twins

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.

Program Leader: Prof. Prem Prakash Jayaraman

Project 1 – AI Models for Digital Manufacturing

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.

Personnel	Name, Project Party
Project Leader	Prof. Yang Xiang, SWINBURNE
Program Leader (Academic)	Prof. Prem Prakash Jayaraman, SWINBURNE
Partner Investigator	Lin He, SYSBOX
Project Personnel	Prof. Dimitrios Georgakopoulos, SWINBURNE Dr. Wei Zhou, SWINBURNE Dr Wanlun Ma, SWINBURNE Dr Sheng Wen, SWINBURNE PhD (to be hired)

Project 2 – Design and Development of Single Source of Truth (SSoT) Knowledgebase to enable data-driven Productivity Improvements

This project aims to design and develop a Single Source of Truth (SSoT) Knowledgebase solution to support productivity improvements, improved traceability and enhanced data analytics.

Personnel	Name, Project Party
Project Leader	Prof. Suresh Palanisamy, SWINBURNE
Program Leader	Prof. Prem Prakash Jayaraman, SWINBURNE
Partner Investigator	Peter Sutton, SUTTON
Project Personnel	Prof. Dimitrios Georgakopoulos, SWINBURNE Dr. Rizwan Abdul Rahman Rashid, SWINBURNE Senior Research Associate (To be hired) Research Associate (To be hired)

Project 3 – Digital Twin system for product consistency in food processing

This project will conduct research to develop novel techniques and approaches for developing Digital Twins for quick and effective production monitoring, analysis diagnostics and prediction. The developed Digital Twins will support real-time predictive analytics for proactive management of production including addressing issues before they adversely impact production, with a specific focus on product consistency.

Personnel	Name, Project Party
Project Leader	Dr. Abhik Banerjee, SWINBURNE
Program Leader	Prof. Prem Prakash Jayaraman, SWINBURNE
Partner Investigator	Mr. Gavin Clifford, EzyChef
Project Personnel	Prof. Prem Prakash Jayaraman, SWINBURNE Prof. Dimitrios Georgakopoulos, SWINBURNE Mr. Liam Bradley, SWINBURNE Yash Pulse, SWINBURNE (PhD Student)

Project 4 – Welding Quality Inspection using Artificial Intelligence and Computer Vision Techniques

The project will develop a product quality assessment solution that combines product digital twins with AI-based computer vision and advanced imaging technologies to automate the inspection process of welded components in each product, increase the inspection accuracy and reliability, as well as reduce training and inspection times.

Personnel	Name, Project Party
Project Leader	Prof. Dimitrios Georgakopoulos, SWINBURNE
Program Leader	Prof. Prem Prakash Jayaraman, SWINBURNE
Partner Investigator	Steven Teofilo, Krueger Transport Equipment Pty Ltd
Project Personnel	AProf. Hailing Zhou, SWINBURNE AProf. Yvonne Durandet, SWINBURNE Prof. Saeid Nahavandi, SWINBURNE Research Associate (to be selected) PhD (to be recruited)