Case Study: a gas distribution network achieves earlier issue detection and lower repair costs with Faculty's AI-powered intelligent gas grid

Gas Distribution Network prevents network issues with Faculty, saving 750 hours per year

Faculty helped a gas distribution network tackle the challenge of identifying operational issues like gas escapes and water ingress only after they were reported by customers. The network collected vast amounts of data, but existing methods relying on manual inspections and basic thresholds were missing early warning signs.

Faculty implemented an AI solution that analyzes network pressure data at 15-minute intervals to detect abnormal behavior indicative of future issues. The system flags these anomalies on a dashboard, allowing engineers to prioritize and resolve problems before they escalate. The solution has the potential to save the network £32m in repair costs and save each planning manager 750 hours per year.