Rheality to commercialise AI-based fluid probe

Rheality has partnered with Clean Engineering to commercialise an AI-based system that optimises fluid production by reducing power consumption and raw material wastage while maximising throughput and product quality.

Rheality
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By measuring how fluids flow and mix through production lines, Rheality’s intelligent sensing system aims to replace process control techniques that have remained unchanged for decades, whereby food, oil and gas, FMCG and chemicals manufacturers can only test what’s in their pipes by halting production.

When traditional test results reveal inadequate processing or substandard products, batches may need to be re-worked or scrapped, resulting in waste of raw materials and energy expenditure to prepare a new batch.

Rheality’s technology allows manufacturers to monitor what is going on inside production pipes in real-time, without having to halt production. This previously inaccessible real-time information allows them to continuously fine tune their production processes, optimising the use of energy and materials.

The system uses a retrofitted passive probe inside the pipe that vibrates according to the fluid flowing around it and generates a fluid ‘fingerprint’. A sensor converts these vibrations into an electrical signal and machine learning algorithms acquire, analyse and convert the signal into a continuous feed of actionable information.

Rheality’s technology was first presented to industry in a series of webinars in 2020, prior to the company spinning out from Birmingham University. This initial publicity resulted in several multinational companies requesting technology trials.

Trials in large-scale manufacturing plants in the UK, Norway, Germany, Spain and North America are now heading towards completion.

Rheality awarded funding to develop ‘acoustic fingerprint’

Dr Francesco Colacino, Rheality co-founder and executive director, said: “These trials revealed immediate benefits for our customers, ranging from product quality monitoring to process optimisation.

"Reducing energy consumption is only the first step in this revolution in fluid production efficiency. Our self-calibrating machine learning algorithm allows bespoke measurements, which respond to our client’s specific needs.

"Not only does data analysis get better over time - and processes can be controlled at more granular level, but customers can also choose what to measure wherever they want along their piping systems. Driving efficiencies in, for instance, end-point mixing, will steadily reduce costs while increasing productivity even further with longer use.”

The Rheality system is said to be fluid agnostic, so can be deployed in production that includes single phase or multiphase environments such as emulsions, oils, gases, slurries, or water, and where the fluid flow is laminar, turbulent or transient. It can be used with any pipe size and in conditions where high acidity or pressure is present.

“We have a streamlined and simplified process for installation that will offer a major benefit to future customers,” said Colacino. “This was developed and tested in trials that ran through periods of Covid travel restrictions and prolonged shut-downs, proving that the system can be installed quickly and operated remotely.”