Application of a product-centred process-independent meta-model for multi-stage production data to enable predictive quality for additive manufacturing

In multi-step production processes with countless information sources, it is vital to accompany process data with meta-information to enable an efficient aggregation of the collected data. The relationships of process- and meta-data has been described through a previously presented flexible and process-independent meta-model, which is especially suitable for predictive quality applications. We propose an enhancement for the attribution of process parameters and quality characteristics. The two novel meta-classes provide information about tolerances and hence increase the process and product model. Our results show how the refined meta-model enhances the mapping of an additive manufacturing process. Further, we introduce an industry-ready implementation and make the code accessible on Github.