Digitalization for homogenizers

Since many years GEA Homogenizer has a strong focus on digitalization in order to offer to customers a comprehensive digital product portfolio with innovative user friendly solutions. 

It has devoted itself both to the study of solutions aimed at predictive maintenance and to the development of systems for optimizing machine operating costs and reducing its environmental impact.

Specifically, GEA Homogenizer has engineered a product dedicated to continuous, real-time monitoring of homogenization quality: the NiSoMate.

GEA NiSoMate is a system capable to measure the product quality of fluid and allows the operator to adjust the operating parameters to achieve the required product quality at the lowest pressure possible, optimizing energy consumption. 

The NiSoMate is able to execute measurement of the physical properties of fluids, using an innovative set of sensors that defines the characteristics of the processed product. Through these parameters we can derive many fluid features including particle size distribution, density, dilution and change of composition.

The instrument can be calibrated directly with the product in order to set the required quality and the parameters are stored in the system as reference against the product analyzed inline. Automation configuration allows GEA NiSoMate to inform the operator and/or process control about any deviation from quality setpoint, reducing waste of product through the entire production run and not by “spot” sampling.

Main features

• Eco-friendly system capable to maximize quality and efficiency to reduce TCO of particle size reduction process
• Sensors are not in direct contact with the product for maximum safety and hygiene
• Suitable for all kind of products and customized to customers’ requirements
• Suitable for all kind of installation: from the lab unit to a large industrial plant, can be installed on new machines, and also as a retrofit solution on existing units
• Hygienic design to meeting the most demanding requirements
• Optimized layout to comply food industry sanitary and safety regulations
• The device can be provided with a machine learning system capable to continuously improve the resolutions