Laser-based methods are considered the standard in particle measurement technology and quickly deliver size distributions. However, this data is often not sufficient for a deep understanding of the process. Modern image-based inline measurement technology provides additional information and enables a more detailed view of the particle system.
Direct Images Instead of Indirect Signals
Laser-based systems measure particle sizes via scattering patterns and thus provide indirect approximations. Image-based sensors, on the other hand, deliver real images of the particles directly in the process. This reveals not only size but also shape, structure, and agglomerate formation. Even in areas with high particle density or complex flows, image-based optics deliver visible and usable information where lasers only provide average values. Anyone who has once seen the actual morphology of their particles immediately understands why this difference is crucial for process control.
Shape and Structure Are Decisive
In many chemical and pharmaceutical processes, the shape of the particles is just as important as their size. Laser devices can only distinguish between spherical particles, fibers, or complex aggregates to a limited extent. Image-based systems provide clear differentiation and quantifiable data on all relevant particle types. In addition, foreign particles or unwanted inclusions can be detected, which significantly improves quality assurance. This not only facilitates process control but also the optimization of crystallizations, mixtures, or suspensions.
Resilience Under Harsh Production Conditions
Laser-based methods are not used inline in many processes because they often can't withstand process conditions such as pressure, temperature, turbidity, or shear forces. Instead, samples must be taken and analyzed offline, which only allows for spot measurements. Image-based inline systems continuously capture particles directly in the process. This allows aggregation, dispersion, or breakage processes to be detected immediately and process adjustments to be made in real time. This reduces scrap, accelerates development, and delivers reliable process information.
AI-Supported Analysis Accelerates Data Evaluation
Laser devices deliver raw data that often has to be laboriously converted into size distributions or volumes. Image-based systems can leverage artificial intelligence to automatically detect and classify particles and instantly quantify parameters such as size, shape, state, or foreign particles. The results are immediately interpretable without the user having to perform complex calculations. This saves time, reduces sources of error, and provides a reliable basis for decision-making in process optimization.
Conclusion
Anyone investing in particle measurement technology today should rely on real process information. Image-based inline measurement technology delivers precise, dynamic, and morphologically meaningful data — directly in the process, in real time, and with AI-supported evaluation. Those who truly understand their particles operate more efficiently, avoid scrap, and can optimize processes in a targeted way.