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Yoghurt, pharmaceuticals, specialty coatings: many products are manufactured in multi-stage, finely tuned steps known as batch processes. These are sensitive operations: poor timing can ruin an entire batch. A research team is developing new concepts to help manufacturers rethink these traditionally rigid workflows. The reason? Electricity from renewable sources comes with fluctuating availability and prices, demanding greater flexibility from industrial production.

Whether in chemistry or technical systems, even the smallest deviations can be dangerous. Deep learning, a method of artificial intelligence (AI), helps to detect such anomalies at an early stage: using large amounts of data, it identifies patterns that often remain invisible to humans.

Fabian Jirasek uses artificial intelligence to predict the properties of pure substances and mixtures. The goal is to help the industry develop new active ingredients and chemicals more sustainably in the future.