The machining of complex aerospace components, such as integral compressor rotors (blisks), involves significant costs, making optimization of this process through simulation an active area of research. The increasing technical quality requirements of the milling process are also refected in the increasing quality requirements of the milling process simulation, which materialize in the twofold demand for more computing power and the ability to handle larger datasets. The rise of quantum computing is drawing attention, as the field might provide methods for optimizing computationally expensive steps of the simulation process. In this paper, a possible application of quantum computing for the machining simulation of multiaxis milling of thin-walled aerospace components is discussed. For this reason, a simulation framework dPart®, used for the milling simulation, is analyzed and the modal analysis, as a resource-intensive computation in the process dynamics simulation, is identified to be optimizable by deploying methods from quantum computing. This paper aims to investigate the challenges that arise when a quantum phase estimation algorithm, with runtime benefits in theoretical toy models, is to be practically integrated into an existing industrial environment. The focus here is whether - and under what circumstances - the runtime superiority of the algorithm can be maintained and practically achieved, even when facing the non-ideality of a real-world engineering application and being integrated into a classical simulation framework. It also examines the technical requirements that a quantum computer must fulfill to provide real performance improvements with acceptable error rates. A concrete implementation for a hybrid approach for calculating the frequency response of arbitrary geometries is laid out. It is inspired by and derived from a similar treatment on systems of linearly coupled oscillators from an earlier publication by the authors.
Schröder et al. (Thu,) studied this question.