Creating resilient assets by forecasting potential risks

Trying to identify potential risks and forecasting the effects of future investments on assets is critical to minimising service failures and maximising value. Ageing infrastructure, climate change, increasing regulation and a growing population can all impact on asset life. With Asset Investment Manager (AIM) you can model the complete lifecycle of assets, anticipating changes and how they will impact on services. The result is better business decision-making, that helps make assets more resilient, reducing service disruption and the risk of regulatory fines.

Questions AIM can help answer

  • How many asset failures can we expect in the next 5 years?
  • What will it cost to maintain our assets over the next 25 years?
  • What happens to our maintenance requirements if deterioration of our assets increases by 0.5%?
  • How many assets in our network are over 50 years old?

Creating Risk Maps to predict asset vulnerabilities

AIM Risk Maps are designed to reveal and visualise the potential vulnerabilities of assets and the costs of service failure. They can support strategical and operational decision-making, providing a transparent, collaborative and auditable approach to making assets more resilient. Creating these maps shows how an asset base is performing now and how investment expenditure may impact the risks to service, and the value it will deliver to end-user. They can combine assets, deterioration and service impact relationships, and intervention costs and benefits in a graphical representation that is easily understood by all stakeholders, asset managers and modellers.


Risk Maps are designed to empower businesses

Risk Maps can be fully configurable by the end-user. Applying our powerful equation editor, you can input any equation required to evaluate risk, service and value. All Risk Maps are stored in one centralised location, enabling all users across the business to quickly visualise what risk and value looks like for each asset type, helping to drive consistency. Importantly, the process is easily repeated when business priorities change.


Advanced statistical distribution and uncertainty

AIM allows for the formal quantification and analysis of uncertainty for every model parameter, before and after optimisation. By including uncertainty distributions within your decision-making framework, you will gain a deeper understanding of the inherent uncertainty around your risks, costs and investment requirements. AIM includes several expert statistical distributions such as Normal/Gaussian, Lognormal, Weibull, Gamma and Chi Squared to help users build advanced deterioration and consequence models.

Request a demo

Request a demo today.