Industry 4.0 reflects the ongoing fourth industrial revolution promotes digital production and transforms today's factories into smart ones to increase production system productivity, and product quality, shorten lead times, and reduced environmental footprints. Hence, industry 4.0 and its related technologies are becoming increasingly important around the globe and in Australia.

The key enabling technologies of Industry 4.0 are cyber-physical systems, the Internet of Things (IoT), Artificial Intelligence (AI), simulation, and digital twin [4]. Digital twin is defined as the digital replica of an object, mapping its characteristics, and aiming to support the design, planning, and control of products and systems.

The idea of a digital twin relies on having a seamless connection between a physical object and its digital twin to improve its performance. However, both academia and industry believe that this seamless integration has not been completely achieved yet and it is needed to reduce and handle the issues of not having complete lifecycle data and data transmission latency to achieve the full potential of digital twin.

On the other hand, the Circular economy concept (CE) revolves around the idea of enhancing resource efficiency through the product lifecycle with various strategies including the known R-strategies: remanufacturing, recycling, reuse, reducing material consumption, and so on.  

In this research project, you have the opportunity to work on various projects as some are listed below and can be re-scoped: 

  1. investigate the application of industry 4.0 technologies such as digital twin and AI to realize smart product life cycle development 
  2. integration of AI and machine learning with Digital Twin in manufacturing systems for data-driven production management
  3. application of AI for supply chain management 
  4. application of Industry 4.0 technologies to realize circular economy 

Mechanical and Manufacturing Engineering

Research Area

Industry 4.0 | Digital twin | Circular economy | Artificial intelligence | Machine learning | Smart production logistic systems | Product life cycle development | Sustainable development  

You have the opportunity to be part of a vibrant team of Industry 4.0 in the school of mechanical and manufacturing engineering. 

The team includes Research associates, PhD students, master's by research, and thesis students which work in different aspects of the explained project with a close collaboration. the team has a vibrant enviornment in sharing the research results on regular meetings.

  • Depending on the chosen project the expected outcome can include: a documented report as critical survey on the literature, a working model (e.g., an AI model), and or a conceptual framework. 
  • Depending on the quality of the work, a journal or conference publication can be an outcome of this project with the guidance offered by the supervisory team.