Sedimentation testing has traditionally been done manually and is prone to human error. Accurate, reliable data can now be achieved through a new technology for measuring the sedimentation and separation efficiency curves of mineral process streams.

The challenge

Accurately measuring sedimentation in settler tanks

WI-SED provides accurate, repeatable measurements of sedimentation and separation curves for different mineral process streams.

One key bottleneck in mineral processing plants is the efficiency of the sedimentation process (solid-liquid separation).

Measuring the sedimentation rate is important for operating plants. For example, the information is used to optimise their reagent use and assist with investment decisions on infrastructure development.

However, current tests are conducted manually by personnel, which is both time-consuming and prone to interpretation errors. Accurate data is needed to inform better decision making.

Our response

A digitally-enabled tool for measuring sedimentation and separation curves

We have developed a portable device for measuring and generating sedimentation and separation curves, called WI-SED.

Measurement data can be viewed from a computer, laptop or smartphone device.

Once samples are collected from process streams such as settler tanks and gravity thickeners, WI-SED automatically records the sedimentation curves by tracking the mud line of liquid slurry.

WI-SED is Wi-Fi enabled to send minerals processing plant operators repeatable and accurate results via their computer or smartphone. It overcomes human interpretation errors and reduces reliance on personnel to make repeated measurements, which saves companies time while producing more robust datasets.

Numerous tests can also be performed within a shorter time period, allowing greater data to be collected.

The results

Greater efficiencies with accurate, robust measurement data

WI-SED saves time and costs by eliminating the need for operators to monitor settling tests and undertake specialist training.

Greater, more robust data means that operators can optimise their processes to achieve higher throughput rates with substantial associated cost benefits.

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