WISER and Fraunhofer ITWM Complete Joint Research on Quantum Machine Learning for Industrial Applications
- Rachel Johnson
- May 18
- 3 min read
Updated: May 19
Washington, DC and Kaiserslautern, Germany | May 19, 2026
The Washington Institute for STEM, Entrepreneurship and Research (WISER) and the Fraunhofer Institute for Industrial Mathematics ITWM have successfully completed a joint research collaboration as part of WISER’s Quantum and AI program, advancing the understanding of quantum machine learning for real-world industrial use cases.
At its core, the collaboration explored how emerging quantum computing methods can support anomaly detection in manufacturing, a critical task for identifying faults in complex production systems.
By analyzing sensor data from industrial equipment, such approaches aim to detect irregularities at an early stage, helping to reduce downtime, improve quality control, and increase overall efficiency. The study focused on practical scenarios such as identifying pneumatic leaks and detecting faults in rotating machinery, illustrating how quantum-enhanced models could complement existing data-driven solutions in industry.
Building on this application perspective, the team conducted a systematic evaluation of Quantum Neural Networks (QNNs), a class of machine learning models designed for near-term quantum hardware. The results show that QNNs can achieve competitive performance, including 87.77% accuracy in pneumatic leak detection and strong ROC-AUC performance on NASA bearing fault datasets. The study further analyzes key design choices such as data encoding strategies, highlighting binary and exponential encodings as effective trade-offs between model expressivity and trainability. The full technical details are available in the corresponding arXiv publication.
“Quantum Neural Networks (QNNs), holds promise for integrating quantum principles into machine learning. However, a critical gap exists in understanding the practical limitations of QNNs regarding trainability and approximation capabilities. Our work provides a roadmap for selecting ansatzes that balance expressivity across both synthetic and real-world datasets, while using limited qubit count to address any noise issues. ” said Vardaan Sahgal, WISER.
Bringing Quantum Machine Learning into Industrial Practice
The collaboration highlights the growing relevance of quantum computing for industrial analytics. As manufacturers face increasing demands for reliability and efficiency, advanced data-driven methods, including quantum-inspired and quantum-native approaches, offer new opportunities for predictive maintenance and process optimization across sectors such as aerospace, automotive, energy, and industrial automation.
“This work demonstrates how quantum machine learning can be applied to real industrial problems today, while highlighting its potential to improve the quality of decision support in complex production environments as quantum hardware continues to evolve,” said Dr. Pascal Halffmann, Fraunhofer ITWM.
This partnership reflects WISER’s mission to accelerate applied innovation through its Solutions Launchpad by connecting emerging technologies with real-world challenges. Combined with Fraunhofer ITWM’s expertise in industrial mathematics, the collaboration provides a structured pathway to evaluate early-stage quantum technologies and translate them into relevant industrial use cases.
Figure 1: A Fischertechnik factory model with artificial leaks in a pneumatic component provided real-world-inspired sensor data for evaluating Quantum Neural Networks in industrial anomaly detection scenarios. © fischerwerke GmbH & Co. KG
About WISER
Headquartered in Washington, D.C., WISER is a not-for-profit organization. The WISER Solutions Launchpad drives applied R&D across quantum, AI, machine learning, and computational science for commercial, government, and academic partners worldwide. The Launchpad builds solutions by exploring quantum speedups, stress-testing quantum-safe security, benchmarking emerging technologies, and developing novel algorithms, thereby cutting through hype and noise. Partners include E.ON, Vanguard, Naval Nuclear Lab, Fraunhofer ITWM and others. Explore opportunities: https://www.thewiser.org/research
About Fraunhofer Institute for Industrial Mathematics ITWM
Fraunhofer ITWM is one of the world's largest industrial mathematical research institutes. Its goal is to further develop mathematics as a key technology, provide innovative impetus, and implement solutions in practice together with industry partners. Methodologically, its research areas are based on modeling, simulation, and optimization.
Solutions Launchpad Contact (WISER)
David Dolhomut
Senior Corporate Partnerships Manager
Email: david.d@wiser.org
Media Contact (Fraunhofer ITWM)
Esther Packullat
Media Relations Manager and Online Editorial
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