Customized mass production may sound contradictory at a first, but it has been a goal of manufacturing for some time now. Realizing this comes with complex logistical challenges that involve solving intricate optimization problems while the production process is in full swing.This complexity pushes classical computers to their limits.
The TAQO-PAM project (Tailored Application of Quantum Optimization for Planning and Control of Assembly and Manufacturing) aims to develop hybrid algorithms that combine classical algorithms with quantum technology to overcome these limitations while at the same time contributing to the development and design of tomorrow's hardware.
The project is led by Professor Wolfgang Mauerer from the Faculty of Computer Science and Mathematics at OTH Regensburg. With a budget of €8.2 million, it is the largest project to date under the leadership of OTH Regensburg funded by the Federal Ministry of Education and Research.
According to Mauerer, a professor of computer science specializing in quantum physics, quantum states are, in some sense, larger than classical states and can interact in classically impossible ways. This gives quantum computers greater power than classical machines. Quantum computers can explore solution spaces much faster than classical machines, opening up new possibilities for real-time optimization of production and intralogistics. This is of particular interest to large industrial companies, as seemingly small adjustments in production planning may combine to significantly enhance economic value.
Mauerer's Laboratory for Digitalization enjoys collaborating with research institutions such as Friedrich-Alexander-Universität Erlangen-Nürnberg, as well-known global industrial leaders such as BMW AG and Siemens AG. Other members of the project team include Science + Computing AG (part of the ATOS Group), who are experts in numerical quantum simulation and the manufacturer of the quantum learning machine used in the project, as well as OptWare, an internationally-renowned "hidden champion" located in Regensburg and Munich, which specializes in industrial optimization.
At OTH Regensburg, Mauerer has assembled a dedicated team that includes four doctoral candidates, computer scientists, mathematicians, and electrical engineers. They collaborate with physicists, mechanical engineers, and other experts from partner companies, who contribute relevant industrial use cases. According to Mauerer, "the interdisciplinary set-up of the team enhances collaboration and facilitates joint learning."
The research team's objective is to develop and simulate specially crafted quantum hardware that can contribute to the development of practical quantum solutions to key industrial problems. Industry requires novel solutions to master production and logistics, as highly individualized production specifications often leave manufacturers unsure about what they will have produced at the end of each day. On the other hand, factories also face enormous combinatorial optimization problems associated with the long-term planning of inter-logistics among different manufacturing sites. Solutions are therefore needed in order to design economically efficient and environmentally sustainable manufacturing plants of the future.
The project is particularly attractive due to the complexity of the problems as well as the combination of theoretical and practical issues involved, says Mauerer. "While problems involving factory data are complex, they are not as far removed from day-to-day reality as, say, those in particle physics. The problems are still a challenge for researchers, and the solutions are highly relevant for industry."
The TAQO-PAM partners are dedicated to developing hybrid quantum-classical algorithms that can be adapted to customized medium-term NISQ (Noisy Intermediate-Scale Quantum) computers. This involves holistic integration of custom-designed quantum processing units (QPUs) into existing scenarios and extending existing factory automation and production planning methods.
The so-called NISQ era refers to a transitional period that features medium-sized, imperfect quantum computers. These devices have too few physical qubits for reliable quantum error correction, making them susceptible to noise that massively affects their real-world utility. Despite these challenges, the hybrid solutions developed in TAQO-PAM aim to bridge the gap until sufficiently powerful quantum processors are available.
The Faculty of Computer Science at OTH Regensburg is regularly ranked as one of the best faculties in Germany by the CHE University Ranking. If you are interested in completing a doctorate at OTH, you can gain further information and advice via the university’s graduate center (in German).
The faculty particularly welcomes applications from visiting professors and lecturers to teach in its English-language computer science and mathematics program.
In addition to co-design, the project has other significant goals in mind. Specifically, the solutions should not require employees (as users of the solutions) to have quantum knowledge. Another strong focus lies on local data processing to avoid the need for sharing sensitive production runtime information with third parties, which would be unavoidable based on the standard cloud deployment of quantum tasks. These factors mean researchers will play a role in shaping the industrial transition into the quantum age, while simultaneously preparing for future stages of development. The research group recently acquired an Atos QLM38 quantum learning machine, which is ideally suited to realizing their research goals. This machine, valued at approximately €1 million, underscores the important role OTH Regensburg has in this field of research. Such high-tech equipment is typically only found at the most well-renowned research facilities such as the Jülich Research Center, the Leibniz Supercomputing Center in Munich, the European Organization for Nuclear Research (CERN), and in Munich Quantum Valley.
The Laboratory for Digitalisation at the Regensburg Technical University of Applied Sciences focuses on research at the intersection between quantum computing, systems engineering, and software engineering.
Its research priorities include
- closing the quantum technology gap between basic research and industrial applications.
- exploring new domains such as database engineering for potential quantum acceleration.
- investigating scientific reproducibility for the future open sourcing of all program codes produced by the research group.
The Regensburg Center for Artificial Intelligence (RCAI) was founded in 2020 and supports interdisciplinary cooperation in AI research and its rea-world application.