Online Characterization in industrial processes refers to the real-time monitoring and analysis of process variables and material properties during production. Unlike traditional methods that rely on offline sampling and lab analysis, online characterization uses sensors, probes, and automated data systems to continuously measure key parameters directly in the process stream. Online characterization enables immediate feedback on process conditions, allowing for instant detection of deviations or defects. This reduces the need for post-production testing and minimizes waste. Since measurements are taken continuously during the process, adjustments can be made on the fly, improving process stability and reducing downtime caused by manual sampling and lab analysis. By catching issues early and minimizing rework or scrapped batches, online characterization helps lower production costs.
Real-time monitoring helps maintain tighter control over critical process parameters, resulting in more uniform products and better adherence to specifications. Another advantage of this in-situ monitoring of critical parameters, is faster decision-making: operators and automated control systems can respond to changing conditions immediately, optimizing throughput and maintaining safety standards without delays. Last but not least is data collection for process optimization: online systems generate large volumes of data that can be analyzed to identify trends, build and improve predictive models, and fine-tune processes for better performance over time. That huge amount of data is nowadays increasingly stored and processed via an Electronic Lab Notebook (ELN), a digital version of a traditional paper lab notebook used by scientists, researchers, and engineers to document experiments, observations, and results. ELNs are becoming standard in many research and industrial environments due to their many advantages over handwritten records: Researchers can type notes, upload images, graphs, spreadsheets, and instrument data directly, can search past entries instantly by keyword, date, or project. Data is encrypted, backed up, and protected from physical loss and multiple users can access, comment, and contribute to notebooks in real time.
As an industrial process, the production of anodes and cathodes for battery cells can, for sure, take advantage of these new ways of monitoring and storing big volumes of critical parameters of fabrication, alongside the entire assembly line. As an example, temperature and vibrations concerning the cathode/anode powder milling step, or temperature and pressure affecting the mixer during the slurry preparation. Inside the coating process, interesting parameters to be monitored in real-time are certainly viscosity, thickness, and density of the slurry, while its porosity and the size of solid particles trapped inside, could be measured in quasi-real time mode, and used to generate good computational models. Furthermore, the transition from laboratory or pilot-scale production to full-scale industrial manufacturing, the insidious process of scaling up, can be dramatically facilitated by all the knowledge acquired throughout the Online Characterization and the ELN data storing framework.
Fabrizio Bernini (BI-REX), Ilaria Olivieri (BI-REX)and Andrea Paolella (UNIMORE)
April 2025