Industrialization of Digital Engineering and Additive Manufacturing

 

In order to achieve resilient industrialized production of AM components, manufacturing and logistics processes must be designed adaptively. One basis for this is, among other things, knowledge of the component geometry at different points in the process chain. In addition to an inventory, digitalization of the components enables an evaluation of the influences of individual process steps on component quality. Predictive quality assurance is thus made possible by adding model and expert knowledge on processes, materials and component functions. To derive this information, the digitized component is compared with the target state. A predictive approach leads this information back into the process chain (CAx chain) and can be used to shorten the development time of new products and to reduce the lead time of existing components.

In a first step, optimization potentials are to be derived on the basis of the status quo. In particular, the optimization of data acquisition and evaluation is in the foreground. With this in mind, methods are to be researched which make the expert knowledge collected available for automated digitisation and evaluation. Process knowledge from previous process steps and model knowledge about the component and the manufacturing process are to be combined in order to achieve dynamic and adaptive digitisation of the component.

The processed data will be used to evaluate compliance with the quality requirements adapted to the respective process step-dependent component condition on the basis of previously defined tolerances.

The integration of automated and adaptive digitization is of interest at several points in the process chain. The measurement data must be adapted to the respective requirements and transferred along the digital chain by means of previously defined interfaces.