<p>Digital workpiece twins are increasingly used to store process knowledge and support the prediction of quality-relevant workpiece properties in machining. In thin-walled aerospace components, residual stresses are a major cause of machining-induced distortion and must therefore be represented in the digital process chain. This paper presents a simulation-based framework for integrating measured residual stress depth profiles into a digital workpiece twin and transferring them to an FE-based deformation simulation. The approach links residual stress measurements, dexel-based material removal simulation, spatial stress mapping, and static structural analysis. Different mapping strategies, boundary conditions, and mesh settings were evaluated with respect to their influence on the resulting deformation prediction. For a high-quality residual stress dataset, the selected setup predicted the dominant positive z-displacement with a relative error of 5.6%. The deformation morphology and the locations of the displacement extrema were reproduced, showing that reliable residual stress input data enable good prediction of the residual-stress-induced deformation tendency. The peak-to-peak displacement range was overestimated by 64.6%, indicating that quantitative accuracy is still affected by measurement quality, depth-profile representation, stress mapping, and FE boundary conditions. The framework provides a basis for residual-stress-aware digital workpiece twins and future process adaptation.</p>