Rheality to commercialise AI-based fluid probe

Rheality has entered into a partnership with Clean technology to commercialize an AI-based system that optimizes fluid production by reducing power consumption and wastage of raw materials while maximizing throughput and product quality.

(Image: AdobeStock)

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

When traditional test results reveal inadequate processing or lower quality products, batches may need to be reprocessed or scrapped, resulting in wasted raw materials and energy consumption to prepare a new batch.

The technology of Rheality enables manufacturers to monitor what is happening in production lines in real time, without having to stop production. This previously inaccessible real-time information enables them to continuously refine their production processes and optimize the use of energy and materials.

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

Rheality’s technology was first presented to the industry in a series of webinars in 2020, before the company emerged from Birmingham University. This initial publicity has led to several multinational companies requesting technological testing.

Trials at large-scale plants in the UK, Norway, Germany, Spain and North America are now nearing completion.

Rheality receives funding to develop ‘acoustic fingerprint’

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

“Reducing energy consumption is only the first step in this revolution in fluid production efficiency. Our self-calibrating machine learning algorithm enables tailor-made measurements to meet our customer’s specific needs.

“Not only does data analysis improve over time – and processes can be monitored on a more granular level – but customers can choose what they want to measure wherever they want along their piping systems. Increasing efficiency in, for example, end-point mixing, will steadily lower costs and increase productivity even further with longer use.”

The Rheality system is said to be fluid agnostic, so it can be deployed in manufacturing that involves single-phase or multi-phase 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 high acidity or pressure conditions.

“We have a streamlined and simplified installation process that will be of great benefit to future customers,” said Colacino. “This has been developed and tested in trials that have endured periods of travel restrictions from Covid and lengthy shutdowns, demonstrating that the system can be quickly installed and operated remotely.”

Abhishek Maheswari
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