As part of the Interreg Digital Twin Academy project, the Faculty of Applied Sciences and the School of Management (HEC) of the University of Liège are working on the design of their digital twin. The team of the Faculty of Applied Sciences works on a project of tool wear monitoring for lathes, involving a digital twin of the tool. On the other side, the HEC team works on a digital twin of an airport to help the logistics management by locating the carts.
Airport ground activities management (HEC Management School)
Airports face various challenges, including those related to air cargo supply chain, resulting in flight delays, equipment damage, and risks to employee safety. Additionally, airports are complex environments where multiple stakeholders need to interact, necessitating effective communication.
With this in mind, HEC Liège, in collaboration with ASL Airlines Belgium and Liège Airport, is currently developing a proof of concept for a digital twin. The digital twin would monitor all the equipment used on-site and optimize resource allocation. It could also serve as a centralized platform to facilitate information sharing among different airport stakeholders and allow ground support operations to run more smoothly. Furthermore, apart from providing a real-time overview of the airport, the digital twin could enable the replay and review of past situations and, eventually, with the help of artificial intelligence models, even predict future scenarios.
To implement the digital twin, a thorough analysis of Liège Airport’s operations was conducted, cataloguing all assets and real-time accessible data. The use of Internet of Things (IoT) technology was favoured, employing sensors to collect information such as equipment location, temperature, and movement. However, there are still technical constraints to address, particularly concerning battery capacity and location accuracy. Research is ongoing to find more efficient solutions. The digital twin also relies on existing databases, such as those containing aircraft arrivals and departures, to faithfully represent the airport. Efforts are being made to gather real-time relevant information by exploring alternatives like the use of cameras and more precise GPS sensors. It should also be noted that, currently, the digital twin only allows one-way interaction: actions in the physical world are reflected in the virtual world, but actions in the virtual world do not yet have an impact on the physical world.
In addition to these advancements, HEC Liège is also focusing on two specific aspects of the digital twin: the interface and the training.
Regarding the interface, it is a key element of digital twins, but there is no consensus yet on its ideal form. HEC Liège has chosen to concentrate on developing a virtual reality platform to enhance immersion and allow users of the digital twin to virtually immerse themselves in the environment using a virtual reality headset. As for training, the digital twin also offers interesting prospects. The effectiveness of virtual reality training compared to traditional training methods has been well established. Therefore, HEC Liège has decided to utilize the digital twin as a training interface as well and is developing VR training modules that will integrate with the digital twin.
Monitoring tool wear (Faculty of Applied Sciences)
Manufacturing machines use tools to machine parts, and unavoidably these tools wear off during the processes. The shape of the tool changes, thus the shapes and the measurements of the produced part. As a result, a drift appears between the measurements (of successive parts), which is small but must be corrected in time to avoid scraps. There are different methods to monitor the tool wear, but the purpose is the same: the machine must compensate the drift caused by the wear. To do so, a correction is usually determined based on the measurements from produced parts and sent to the machine (for the project, we mainly focus on lathes).
The interest for a digital twin in this case is the ability to concentrate all the information to analyze the wear of the tool and automatically apply the required corrections. The data sources are the measurements of the produced parts and the data from the process (machining parameters such as the feed rate and environment data such as the temperature). The decision-making part of the digital twin uses the estimated measurement of the next part to determine the correction that will be applied to the lathe. The estimated measurement is mainly computed with the drift determined by the parts previously produced by the tool, however it can also be determined by the drift of an old tool that had the same process profile (hence the interest for the process data).
The first version of the digital twin was actually not the one presented. At first, the digital twin was supposed to be fed by the measurements only, but it appears that the accuracy of the measurements has a significant impact on the drift computations. In fact, our model was not able to provide a reliable correction for the first parts produced by the tool, which is why we decided to save the results from digital twins of previous tools (which were first supposed to disappear once the tool was discarded) and use it as a temporary model. This update implies that the process data must be considered, but it cannot be linked to a digital twin of a tool. In consequence, the digital twin solution had to be completely redefined as an aggregate of two digital twins (solution called “aggregated digital twin”): one for the tool and one for the lathe. In our present solution, the digital twin of the tool computes the correction based on the information provided by the digital twin of the lathe monitoring the process.
These projects are being carried out within the digital twin academy project. This project is carried out within Interreg V-A Euregio Meuse-Rhine, with subsidy from the European Regional Development Fund.