Industrial rubber compounds usually are stored ready for processing. Thus all components, for instance, fillers, curing agents, and stabilizers, are merged prior to storage, which causes chemical and physical events (e.g. filler aggregation, consumption of inhibitors, or loss of volatile components) to start prematurely. These may significantly alter both the processing behavior of the rubber compounds and the degree of cure (mechanical props) in the final injection molded part. In this work, we evaluated the influence of storing conditions on the processing behavior directly in the injection molding machine. We used a carbon-black filled, Sulphur-curing NBR compound which was stored at 5 °C for 6 months and then split into two fractions. While fraction A was stored for another 4 months at 5 °C, fraction B was stored at 25 °C for the same time. Subsequently, using a Rubber Process Analyzer (RPA), we determined the impact of storage on the viscosity and the curing behavior. Additionally, we manufactured test specimens using both fractions separately while gathering specific process signals of the injection molding machine in real time. In a further step, compression sets were obtained from the test specimens. From the process signals, we calculated specific features and analyzed their ability to detect storage-induced process changes. Features based on the total work of dosing as well as total work of injection performed best. These correlated well with the RPA and the Compression Set results. In a next step, we will evaluate their usability for a product-adaptive closed-loop process control. In other words, the detectability of deviating compound properties in the dosing step would allow for adapting subsequent molding phases accordingly. This would increase the yield of rubber injection molding by ensuring stable part quality in spite of differently stored batches.