It is said to have the potential to save the industry countless hours and millions of pounds a year.
The strength prediction engine was developed in collaboration with BAM Nuttall, using funding from an Innovate UK grant awarded last year. The system is already being used on BAM Nuttall’s London City Airport expansion project.
Development of the system was made possible by Converge’s access to a huge data set on concrete performance, paving the way for the commercial application of machine learning to monitor and predict material performance in a live project.
BAM Nuttall head of innovation Colin Evison said: “This advancement in construction technology is a game changer. The Converge prediction engine gives us insight into material performance we didn't think possible. We are delighted to be Converge’s industry partner in bringing this exciting new tool to market.”
Since its inception in 2014, Converge has focused on bringing efficiencies to site and shortening concrete cycles with real-time strength data. The company found that, whilst the alerts and live data generated bring significant project management benefits, resultant actions often weren’t happening until many hours after critical strengths were reached. Converge product lead Sam Ellenby said: “Our users were waiting for concrete to hit a critical strength before scheduling the next activity, but this often meant that the site teams needed to strike formwork or tension the slab were deployed in other areas when the time came to act. Thus, critical actions were frequently delayed.”
While such delays are small, when accumulated across hundreds of cycles they result in weeks of lost potential progress, said the development team. When concrete sits on the critical path, the costs associated with these time lags costs the industry millions of pounds every year.
The predictions engine combines local weather data, a database of historical concrete curing data, and the Converge concrete monitoring platform’s real-time measurements from the pour. This gives Converge the ability to predict the time the concrete will reach strength with an accuracy of +/- 5%, several days in advance. “The result of this immense predictive power is that teams can plan to act precisely when needed,” said the developers.” This improved productivity keeps projects on track and, ultimately, can save millions of pounds.
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