The knowledge explosion in all areas is both an opportunity and a risk. In order to shape the effects as positively as possible and create sustainable added value, the amount of information must be processed in a targeted manner and important content must be separated from ignorable content.
In the automotive industry and especially in the development of new components, it is possible to look back on many past projects and thus knowledge. However, the decisive factor is whether this information is available in a suitably processed form or the knowledge is even held by just a single expert. A new and intelligent method is therefore required to analyze existing data appropriately and at the same time prepare it ideally for further applications, such as use within forecast models based on Artificial Intelligence (AI). To achieve this, several steps need to be taken.
Firstly, it is possible to perform a suitable segmentation of the component. The aim is to detect areas in a component where features and form elements are found. Other remaining regions are ignored after the inspection by segmentation and voxelization: There is no sustainable valuable knowledge here.
Subsequently, the voxelization of the component takes place, which results in the three-dimensional component or Computer-Aided-Design (CAD) file being mathematically readable and thus a kind of translation takes place. This is done by rasterizing the component based on a previously selected resolution and other upcoming steps.
Finally, the segmented and relevant areas are analyzed accordingly. This can be done according to corresponding previously defined guidelines or, for example, by using a suitably trained AI. The advantage is based in the mathematical readability, which is now given by the voxelization that has taken place.