Because of rising demands for economic and sustainable product life cycles, the relevance of efficient repair processes increases [
1]. An example for products for which a repair is highly motivated are Blade integrated disks (Blisks) made from Ti-6Al-4V. They are commonly used within compressor stages of jet engines, because of a better power-to-weight ratio. Due to their integral construction and complex geometries, flexible and efficient repair processes are needed if one blade is damaged during operation. Depending on the type of damage, an additional material deposit by welding or brazing might be required to build up the damaged region. Afterwards, the excessive deposit material has to be removed to restore the original geometry. This material removal is carried out using grinding or milling processes. The so-called re-contouring process differs from new part production, because of the uniqueness of each repair case and often-different material properties due to the welding or brazing filler [
2]. The uniqueness of each repair case also prevents running-in processes, which are commonly used in new part production. Thus, the milling process has to be designed individually for each repair case beforehand. Therefore, a virtual process simulation is considered beneficial [
2]. For re-contouring, 5-axis ball end milling is typically used, due to its geometric flexibility and accessibility [
2]. Because of vibration prone parts and the often required use of slender tool holders, a stability prognosis of the milling process is required for designing sound re-contouring processes. Additionally, the resulting geometric accuracy and surface topography is of superior importance to minimize scrap and flow loss [
3]. In literature, methods exist to predict process stability and surface topography, which can be categorized in analytical and numerical approaches. Analytical methods are often limited to calculate stability lobes without predicting geometric shape errors [
4,
5]. They are often restricted to specific use cases, too. Numerical methods are called material removal simulations (MRS). MRS can predict surface topography and process stability, if a dynamic model is used. Their main advantage over analytical models is their flexibility regarding process kinematics and workpiece geometry. Furthermore, the accuracy of stability prognosis is higher, because non-linear effects can be considered using time-domain discretized simulations. However, they are less efficient and need higher computation time [
6]. For re-contouring, the application of numerical-simulations is favourable, because of the flexibility needed regarding the complex workpiece geometries as well as the calculation of the engagement parameters considering true milling kinematics. Existing MRS use voxel, dexel or constructive solid geometry (CSG) to discretize the workpiece. The approach by Surmann is one example for the use of CSG including the consideration of tool dynamics [
7]. Kersting et al. extends the model by considering workpiece vibrations [
8]. However, in both approaches, the cutting edges of the tool are not modelled discretely, preventing the prognosis of surface topography errors due to e.g. cutting edge chipping or helix angle effects. Hense presents a hybrid approach [
9], which is based on the works of Siebrecht and Odendahl [
10]. Thereby, a CSG workpiece model is used to determine the engagement conditions for calculating process forces with Kienzles force model. This allows deriving the displacements of the tool-workpiece dynamic system using sets of damped driven oscillators. An additional multi-dexel workpiece model is used to consider effects of the discrete modelled cutting edges on the surface topography. However, the long computation time needed is stated as problematically [
9]. Montgomery and Altintas presented a MRS considering the flank face—workpiece contact and the resulting ploughing forces [
11], which were assumed to be proportional to the yield strength of the material [
12]. The workpiece surface could be predicted with a high accuracy. Another MRS considering the contact between flank wear and the workpiece surface was developed by Ko [
13]. Stability charts for worn tools were in good agreement with experimental stability charts. However, the surface resulting from the milling process was not analysed. This paper presents a dynamic material removal simulation, which is able to run in real-time, eliminating the disadvantage of long computation times of existing approaches. Despite analyzing process stability, the simulation is able to predict high-resolution surface topography including effects of discrete-modelled cutting edges. This allows an optimization of the re-contouring process also with respect to geometric accuracy.