Project duration: 01.10.2021 - 30.06.2024 | Website: adaproq.com

Due to the current industrial change, the automotive industry is facing special challenges to meet new drive and product concepts as well as sustainability requirements. Further challenges are the increasing component complexity as well as the high quality requirements. For this reason, companies must expand their adaptation capabilities and establish resilient production technologies. Up to now, quality assurance has often been carried out heuristically or on the basis of random samples.

AdaProQ aims to drive the development and validation of generic methods to control manufacturing quality within complex process chains. A holistic view of large parts of the existing process chain enables a complete re-evaluation of manufacturing tolerances. Through the use of artificial intelligence, efficient optimization and sensory as well as active components, complex manufacturing processes are enabled to adapt themselves in such a way that they react adequately and autonomously to changing boundary conditions. Component quality improves and the reject rate is reduced.

Merantix Momentum uses machine learning to develop methods that show correlations between process parameters and resulting quality. The focus on interpretable methods enables the application partners in the project to understand the correlations in detail and thus optimize production processes more quickly.