Applications for quantum computing in the EniQmA project
As part of EniQmA, three use cases are being developed to both test the newly designed EniQmA tools and to identify potentially interesting applications for quantum computing, as well as to further develop the necessary algorithms.
Anomaly Detection in Production: The potential of Quantum Machine Learning (QML) for anomaly detection is being analyzed. This involves considering both predictive maintenance and anomaly detection through the analysis of images for automated quality control.
Sustainability in Aircraft Design and Operation: The tools for material simulation and structural optimization are set to be enhanced using quantum computing. This will also improve the development of high-performance, lighter components for aircraft, enabling material optimization and fuel savings in operation.
Train Routing Optimization: The goal is to optimize train scheduling based on a given timetable. The number of trains and empty runnings are minimized while the network resilience is maximized. For this, the optimization problem is transformed into QUBOs (Quadratic Unconstrained Binary Optimization) and solved using hybrid quantum computing methods.