Predictive failure and analytics

Reactive maintenance is a significant risk to an organisation and its success depends on meeting legal, regulatory, economic and social requirements. Sewer blockages, burst water mains and equipment failure, for example, result in serious impacts for customers and significant direct and indirect costs for asset owners. Predictive analysis helps companies to understand the level of risk at which they are operating, and to plan and justify capital investment in the asset base to maintain or improve levels of service.

We have developed techniques and tools across a variety of analytical platforms to analyse water and sewerage pipes and above ground assets. By modelling deterioration and reliability, we have helped some of the UK’s largest water companies, including South West Water and Yorkshire Water, develop more effective asset renewal and proactive maintenance programs. For example, using our sewer deterioration model, we have increased the efficiency of costly CCTV survey work and improved pipe defect detection rates from 20 to 50 percent.

Our approach uses engineering insight alongside robust analysis to determine the underlying factors that contribute to asset performance and failure. We amalgamate and process vast amounts of information from disparate corporate datasets and use both traditional and machine learning algorithms to analyse asset reliability, service failure and the consequences for customers and the environment.

Our predictive models have empowered asset owners and operators to make data-driven decisions to better manage their assets and forecast asset performance more effectively.