Quantum optimization of quality control in automotive production

In automotive, quality control presents a complex challenge: Each car undergoes various quality control tests, which must be completed in a specific order. The workflow is constrained by several factors, including the number of workers available over time and some tests being dependent on others being completed first. This presents a daily challenge in automotive, known as an NP-hard scheduling problem, which is difficult to solve with traditional computers.Volkswagen, an automotive pioneer in quantum computing, investigated this industrial use case, utilizing the QMware cloud. The research team compared problem instances with a number of quantum, classical, and hybrid quantum-classical algorithms. The team developed a novel QUBO to represent the scheduling problem, illustrating how the QUBO complexity depends on the input problem. They present a decomposition method for this specific application to mitigate this complexity, showing how effective the approach is.

Picture of a car on the assembly line in automotive production

If you work in automotive and quality control testing presents a challenge to your business, the QMware cloud platform provides a new potential solution for optimizing these complex quality control testing tasks. The QMware quantum computing cloud utilizes classical high-performance computers along with simulated and native quantum computing processors. By integrating the most advanced quantum technologies available, the QMware platform offers the next level of computing performance.

QMware is the leading European quantum cloud provider. Contact us today to learn more about how the QMware platform can transform your organization’s productivity and efficiency.

Explore our research papers

Get insights to QMware's hybrid quantum computing approach.

See publications

Get in touch

Reach out to us for more information.

Contact us