One technology.
Many applications.

Loss Monitoring

Loss monitoring can increase yields and grow profits. For example, there’s anecdotal evidence that some dairy factories have product losses of up to 5%. Some of their hyper-efficient competitors tell us they have reduced losses to 0.1%. This substantial gain is possible with loss monitoring systems using Quadbeam’s multi-beam suspended solids sensors.

Product phase or interface transition

Prevent product wastage and save money by controlling phase or interface transition. With precise measurement of suspended solids, you can set an exact cut-point and optimise the transition between phases, giving you highly repeatable process control. Quadbeam’s multi-beam suspended solids sensors identify this transition with unrivalled accuracy.

Milk Fat Monitoring

Accurate monitoring for milk fat concentration can significantly speed up production, reduce fat losses and provide a more consistent product thanks to a more repeatable process. Quadbeam’s multi-beam suspended solids sensors offer these advantages thanks to their unrivalled accuracy.

Yoghurt

Quadbeam sensors can create efficiencies at multiple points in the yoghurt manufacturing process, achieving significant savings.

COW water

Whether you’re going to re-purpose COW water or simply send it to waste, solids carry-over can create challenges. Quadbeam’s multi-beam suspended solids sensors can help in both scenarios.  

Heat exchanger

Effective monitoring can improve heat exchanger performance and protect the heat exchanger itself, creating efficiency gains that save money. 

Solids recovery

This application is best-suited to larger plants for processes like milk powder and cheese, and we know of customers that have seen returns of over $150,000 per year from this installation.

Separator control

Some plants use single-beam sensors for separator control, but they contain inferior technology and may not offer the accuracy needed for reliable process control. Quadbeam sensors use multi-beam light and a ratio-metric algorithm to self-compensate for common sources of measurement error, and they’re extremely robust.