Quantum computing (QC) is a technology developing rapidly in research, but has also raised initial expectations in industrial applications. The manufacturing industry is one of the central German economic sectors of outstanding importance, which has to meet highest quality standards in order to be competitive. In order to avoid errors in manufacturing, simulations are used to derive optimized parameterizations of machines. Simulations are based on physical and material science models and systems of equations, which place considerable demands on engineering knowledge in modeling and the resources for simulation calculation. Consequently, in particular SMEs are often overburdened with the use of such approaches. In this context, QUASIM will test a QC approach that will make simulations faster and more practical. Modeling efforts shall be reduced by Quantum Machine Learning. For pure acceleration, an approach combining finite element method with QC will be investigated. By comparison with previous approaches, innovative solutions based on QC will be designed, implemented, integrated into low-threshold services and made available in distributed environments via GAIA-X environments. This should also enable manufacturing companies to access QC services, which themselves have only limited expertise in simulations in manufacturing.
Partners
Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI) GmbH (Koordination), Forschungszentrum Jülich, Fraunhofer-Institut für Produktionstechnologie IPT, ModuleWorks GmbH, TRUMPF Werkzeugmaschinen GmbH + Co. KG
