Food and Beverage Business
Manufacturing

AI-Powered Design for Industrial Processing Equipment Unveiled by Birmingham

AI-Powered Design for Industrial Processing Equipment Unveiled by Birmingham AI-Powered, Birmingham, design, industrial processing equipment Food and Beverage Business

The University of Birmingham Enterprise has launched EvoPhase, a cutting-edge service that optimizes process equipment used in food manufacturing. EvoPhase utilizes evolutionary AI algorithms and advanced simulations to enhance the design of mixing blades and blending vessels, resulting in improved efficiency and cost savings for various industrial applications.

This unique AI-led approach, known as “evolutionary design,” can be applied to a wide range of process equipment, including mills, dryers, roasters, coaters, and stirred tanks. By leveraging innovative technologies and expertise from Birmingham’s School of Chemical Engineering, EvoPhase tackles challenges in traditional R&D methods that have proven difficult to overcome.

“Up to 50% of the world’s products rely on granular materials in their manufacturing processes, yet these materials are complex to characterize and understand,” says CEO Dominik Werner. Granules exhibit peculiar properties, transitioning from solid to liquid-like and gas-like states depending on their containment and external influences. This complexity makes granules the most intricate form of matter to process.

To address this complexity, EvoPhase employs a novel AI technology called highly-autonomous rapid prototyping for particulate processes (HARPPP). This technology mimics natural selection to generate and test evolved designs, allowing users to optimize multiple parameters simultaneously without compromising on key targets such as power draw, throughput, and mixing rate.

In addition, EvoPhase utilizes a numerical method called the discrete element method (DEM) to predict the behavior of granular materials. This method computes the movement of individual particles and can be further validated using positron emission particle tracking (PEPT), a technique pioneered at Birmingham that draws inspiration from medical imaging.

Leonard Nicusan, Chief Technology Officer at EvoPhase, explains that their comprehensive range of technologies enables them to offer material characterization, digital model development, experimental imaging and validation, process optimization, geometric design optimization, scale-up, and predictive model development. This approach holds significant potential for all industries involved in powder, granule, and fluid processing, offering substantial cost savings through increased energy efficiency, improved mixing effectiveness, and enhanced throughput.

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