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TAQO-PAM: Tailored Application of Quantum Optimisation for Planning and Control of Assembly and Manufacturing

This project addresses the real-time optimization of production and intralogistics, in particular of modern matrix manufacturing facilities, using hybrid quantum-classical algorithms adapted to customized medium-term NISQ hardware. This is done by holistically integrating problem-specific adapted quantum processing units (QPUs) into existing scenarios and by extending existing factory automation and production planning methods.

The development of systems that can be integrated into existing technologies at the operational level allows QPUs to be used in latency- and determinism-dependent scenarios. The focus on local data processing avoids the need to share sensitive production runtime knowledge and data with third parties. Based on the assumption that suitable custom QPUs will be available in the medium term, the project explores quantum algorithms for optimizing manufacturing tasks, considers the integration of quantum computing into industrial processes, and makes the technology usable for users without deep quantum mechanical and quantum computing knowledge. By systematically transferring real problems from industry, the advantages of quantum algorithms are to be combined with advantages of classical algorithms and thus industrially usable use cases are to be successfully solved.

For more information, please refer to the project's homepage.

This project is sponsored by the Federal Ministry of Education and Research.


To Appear IEEE Conference
Effects of Imperfections on Quantum Algorithms: A Software Engineering Perspective
Felix Greiwe, Tom Krüger, Wolfgang MauererProceedings of the IEEE Quantum Software Week2023.
PDF [BibTex]
To Appear IEEE Conference
Influence of HW-SW-Co-Design on Quantum Computing Scalability
Hila Safi, Karen Wintersperger, Wolfgang MauererProceedings of the IEEE Quantum Software Week2023.
PDF [BibTex]
To Appear Conference
Optimization Problems in Production and Planning: Approaches and Limitations in View of Possible Quantum Superiority
Maximilian Zwingel, Oguz Kedilioglu, Sebastian Reitelshöfer, Wolfgang MauererProceedings of the 8th MHI ColloquiumSpringer2023.
SIGMOD A* Tutorial
Quantum Machine Learning: Foundation, New Techniques, and Opportunities for Database Research
Tobias Winker, Sven Groppe, Valter Uotila, Zhengtong Yan, Jiaheng Lu, Maja Franz, Wolfgang MauererCompanion of the 2023 International Conference on Management of DataAssociation for Computing Machinery2023.
PDF 10.1145/3555041.3589404 [BibTex]
QPU-System Co-Design for Quantum HPC Accelerators
Karen Wintersperger, Hila Safi, Wolfgang MauererProceedings of the 35th GI/ITG International Conference on the Architecture of Computing SystemsGesellschaft für Informatik2022.
PDF https://doi.org/10.1007/978-3-031-21867-5_7 [BibTex]