But when it comes to truly understanding processes, grasping their dynamics, and making optimizations, laser devices quickly reach their limits. Modern image-based inline measurement technology offers decisive added value here.
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 allows not only the size to be detected, but also the shape, structure, and agglomeration. Even in areas with high particle density or complex flows, image optics provide visible and usable information where lasers only provide average values. Once you have seen the actual morphology of your particles, you immediately understand why this difference is crucial for process control.
Shape and structure are crucial
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.
Resistance to harsh production conditions
Laser-based methods are not used inline in many processes because they often cannot withstand process conditions such as pressure, temperature, turbidity, or shear forces. Instead, samples must be taken and analyzed offline, which only allows for selective measurements. Image-based inline systems continuously detect 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 waste, accelerates development, and provides reliable process information.
AI-supported analysis accelerates data evaluation
Laser devices provide raw data that often has to be converted into size distributions or volumes, which can be a time-consuming process. Image-based systems can use artificial intelligence to automatically detect and classify particles and immediately quantify parameters such as size, shape, aggregate state, or foreign particles. The results can be interpreted immediately without the user having to perform complex calculations. This saves time, reduces sources of error, and provides a reliable basis for decision-making for process optimization.
Conclusion
Anyone investing in particle measurement technology today should focus 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 waste, and can optimize processes in a targeted manner.