Binnies, Williams Grand Prix Technologies, and JuliaHub have announced a partnership to introduce scientific machine learning (SciML) to the UK water sector. This collaboration aims to help water companies shift from reactive to predictive asset management using existing data, marking a first for the industry in the UK.
The partnership brings AI technology from the motorsport, aviation, and aerospace industries to assist water companies in preventing asset failures before they occur. The move aligns with the recommendations of the recently published Cunliffe Review, which urges water companies to proactively assess asset condition even when data quality is limited.
As the UK water sector prepares for its next investment cycle (AMP8), there is a growing consensus that predicting failures earlier and taking a more proactive approach to asset health are crucial. However, challenges remain, particularly around poor data quality, which limits the effectiveness of current predictive models.
The partnership brings AI technology from the motorsport, aviation, and aerospace industries to assist water companies in preventing asset failures before they occur
To address this, Binnies formed a partnership with Williams Grand Prix Technologies and JuliaHub, combining their sector expertise and engineering capabilities with SciML. This advanced technology is designed to function in complex engineering environments where traditional machine learning may not be as effective. Unlike traditional machine learning, which relies on large amounts of clean historical data, SciML integrates scientific principles like fluid dynamics and thermodynamics to predict asset behaviour. This allows for more accurate predictions, even in the absence of complete data or when sensor deployments are limited.
SciML has already been successfully applied in sectors such as motorsport, aviation, and aerospace. For the water industry, it promises to reduce the need for costly sensor installations or extensive data cleaning, allowing companies to make better use of the data they already have.
The partnership is not just about introducing new technology, but also about shifting the mindset in the sector. It encourages a move from reactive to predictive operations, enhancing risk management and investment decisions. This new approach aims to improve operational resilience across the water industry.
Early projects with Southern Water and Anglian Water have demonstrated the technology’s potential, showing that SciML can help companies achieve predictive asset health at scale, even with limited data. This approach supports the goals set out in the Cunliffe Review, which calls for proactive management of asset health to stay ahead of potential failures.
Through this collaboration, Binnies, Williams Grand Prix Technologies, and JuliaHub aim to reshape the approach to asset health in the UK water sector
Tom Ray, Director of Digital Products & Services at Binnies UK Ltd, commented, "This partnership could fundamentally change how the water industry approaches asset health. For the first time, predictive insight doesn’t require perfect data, and that’s a breakthrough the industry’s been waiting for."
Selin Tur, Managing Director and Chief Technology Officer of Williams Grand Prix Technologies, said, “At Williams Grand Prix Technologies, we live by the same principles that fuel Formula 1 – speed, precision, and relentless innovation. Scientific machine learning empowers us to predict complex system behaviours even from imperfect data, giving us the foresight that’s critical in high-stakes engineering. We’re thrilled to bring this capability to the UK water sector with Binnies and JuliaHub, transforming how asset health is monitored and helping the industry shift from reactive fixes to proactive resilience.”
Deepak Vinchhi, Co-Founder and COO of JuliaHub, added, "SciML is revolutionising how critical industries such as aerospace, semiconductor, pharmaceutical and energy use AI. It thrives where traditional models fail, and we’re thrilled to see it applied to critical water infrastructure."
Through this collaboration, Binnies, Williams Grand Prix Technologies, and JuliaHub aim to reshape the approach to asset health in the UK water sector. Their work with SciML offers a way for water companies to predict failures, optimize performance, and invest more confidently, even when data is limited.
