Digital twins are virtual representations that serve as a real-time digital counterpart of a physical object or process. They can be continuously updated using real-time data and use simulation to enrich information about the process modelled. Digital twins can be used to support decision making, increase efficiency, identify trends, raise alerts about process problems, and be used as a simulation tool to test responses to different operating scenarios.
A major plan within FEnEx CRC is to build the LNG Futures Facility, a small-scale LNG plant as a testbed for new LNG and hydrogen technologies and processes, with a digital twin that permits accurate simulation and optimisation of its operational behaviour.
Program 3: Digital Twin Feasibility Study
This project is a necessary first step towards the development of a digital twin model for the LNG plant within the Futures Facility. By being able to track in real time the material flow and behaviour within a LNG train, production efficiencies can be improved through:
- real-time optimisation of mixed refrigerant compositions and compression duties to maximise cooling process efficiency and produce more LNG with less power consumption
- exposing the onset of solids formation in cryogenic heat exchangers to enable operators to take action to avoid blockages
- providing data to feed self-tuning process control systems, better accommodating changing feed gas compositions and improving the control of LNG scrub columns and cryogenic heat exchangers
- providing data in near-real time to a predictive maintenance system, leading to reliable replacement parts prediction and reduced spares inventory.
Working with Enterprise Transformation Partners, this project will explore flexible, low-cost software solutions for digital twins that could be used ‘out of the box’ or to build a bespoke digital twin solution.
Using the detailed physical design of the FEnEx CRC Futures Facility Plant as the basis for the digital twin, the first stage is to define the process model (including processes, inputs, outputs, equipment etc.) and identify and document all of the functional and non-functional requirements of the digital twin. This specification will then be used to analyse how well existing digital twins products can meet the requirements, and identify any gaps that would need to be closed.
The second part of the project will assess the feasibility of using the Manufacturing Intelligence digital twin, which has been developed for the mining industry, and identify how well it meets the requirements. Any functionality gaps will be identified and would need to be addressed in a subsequent project before it could be used in field trials with the Future Facilities Plant.
Partners: Enterprise Transformation Partners, The University of Western Australia, Curtin University and Future Energy Exports CRC
Project Researchers: Dr Peter Falloon, Dr Luke McElroy
Duration: 6 months