Data pipelines for product function prediction in circular factories

Optimizing global material flow and resource consumption is a key goal of the circular economy. Regarding production, the circular economy relies on the targeted reprocessing of used products, requiring extensive product data for informed decisions. However, the available data regarding distinct product generations and variants is fluctuating, and necessary data can be scattered or incompatible. The problem is that a comprehensive data processing method to deal with the mentioned requirements is missing. Therefore, a concept for designing data processing pipelines is presented and demonstrated in a circular factory for angle grinders. These pipelines focus on function prediction tasks and showcase the benefits of adapting pipeline compositions, drawing from existing data analysis.