The Challenge

Equipment failure does not happen in a vacuum. Often, catastrophic failures or loss of containment occur due to a series of events resulting from multiple layers of protection breaking down. The key to advancing our ability to predict the multitude of potential outcomes from any combination of these layers failing lies in advanced analytics. To borrow a metaphor, consider your fuel tank gauge. As a standalone KPI, the gauge tells you when your tank is approaching empty. However, it does not automatically tell you the various scenarios and consequent risk you could encounter when you run out of gas. Maybe it happens right beside a gas station, or maybe it happens in the middle of nowhere with no cell reception as you’re already running late for an important meeting.

Being able to detect that the tank is running low is one element of integrity management. Being able to predict and plan for the various outcomes that are likely to occur if it does is quite another. That is the aspiration of advanced analytics with AIM – and KPIs are the vehicle to achieve it.

Leveraging KPIs with AIM

When used to measure the efficacy of various elements of your AIM program – e.g. risk assessment, inspection scheduling, corrosion monitoring locations, etc. – KPIs provide a useful summary of how effective your practices really are, for better and for worse. They can be used for future analytics to predict future trends, events and behaviours. These analytics are composed of predictive data analytics, big data (e.g. loads of process data), and data mining.

Specifically, in the case of corrosion, having the data points for these analytics could potentially be useful in analyzing thickness readings and their trends to better understand how corrosion rates are associated with process conditions – thereby enabling you to predict wall thickness changes.

Another benefit is the potential for corrosion models that utilize analytics to predict when an operation will move into the corrosive region for the model.

There is also the potential for models that calculate risk changes based purely on these analytics.

The underlying power of advanced analytics in helping you better understand not only when the tank is running low, but also all of the possible scenarios which could occur– and how to ensure that the best scenario is the final outcome – is truly the future of mechanical integrity. In order to be ready at the advent of these trends as they approach, it is crucial to build your arsenal of the key data that will be utilized to create them: KPIs.

By employing an AIM software that utilizes KPIs and enables analysis of database equipment information, the following could be derived to confirm system performance: