An example of such simulation work is shown in the picture: The presented model is a set of 3D printed Ti-based half-shell bearing components, finding the application for instance, in the engines of the space rockets.
Left image is the result of a Computer Aided Analysis (CAA), which assesses as-is process performance. In general, when considering an optimal process performance, the CAA step would show quiet uniform color distibution around our model. In this case, the color distribution varies, stating that we are dealing with a high degree of inhomogenity. Depending on our interest, this inhomogenity might be defined as non-homogenous current density/potential distribution, or metal dissolution or surface roughness. Each of the colors will then stand for: red – too high value, green – optimal value, blue – too low value.
Right image is the result of a CAE step, where an appropriate mitigation strategy has been implemented based on the outcome of the CAA step. It can be clearly seen that a great tactic has been used, allowing us to optimize the inhomogenity observed in the central part of the bearings (notice color change: blue to green).