What is an ARA?

You probably already leverage common methodologies such as Failure Modes and Effects Analysis (FMEA), Risk-Based Inspection (RBI), or Reliability Centered Maintenance (RCM) to manage the reliability of your facility. However, how confident are you in the forecasted reliability of your facility? Are you able to use your data to drive reliability decisions for your entire facility?

With Quantitative Reliability Optimization (QRO), your facility can take the next step in achieving facility-wide reliability objectives. QRO is a new dynamic reliability approach that bridges existing first principles reliability models with new data science, multi-variate analysis and system-based optimization to drive improved facility performance balancing availability, process safety, and spending performance.

QRO is comprised of four elements: Asset Risk Analysis (ARA), the Lifetime Variability Curve (LVC), Forecasting System Availability, and Reliability Simulation and Performance Optimization. The cornerstone of QRO is the ARA.

An Asset Risk Analysis (ARA) integrates first principles engineering analysis and asset data with field execution limitations and operational constraints to build the foundation for system reliability analysis and optimization. ARAs create a cause and effect link between all assets’ functions, failure modes, and failure mechanisms to identify the reliability and maintenance tasks that are needed to mitigate failures.

Typical reliability methodologies measure different asset classes through different programs, which can lead to wasted spending and unmanaged risk. ARAs enable a consistent, data-driven analysis across different asset types in a single platform. By evaluating assets consistently and quantitatively in a single platform, facility leaders can now effectively compare risks or prioritize resources across different asset classes.

How Does an ARA Work?

First, an ARA analyzes an asset’s function and specific performance requirements. Next, failure modes and potential failure mechanisms are evaluated, and the ARA establishes causal links between the two. The ARA then analyzes critical reliability data to determine the basis for the asset’s probability of failure. Next, consequence of failure scenarios are documented for production impacts, HSE risk, and repair and replace costs, and links the data and maintenance tasks needed to prevent the failures from occurring.

As a result, an ARA implementation gives facilities better insight into how they can use already available data to implement a more proactive approach to maintenance and reliability.

Example of an ARA

A fin fan heat exchanger is comprised of both fixed and rotating pieces such as header boxes, fans, and motors. Today, these components are managed by RBI and RCM programs separately. RBI is typically more quantitative while RCM is more qualitative. As a result, facility leaders often have a hard time prioritizing limited resources across asset types to prioritize what tasks need to be completed when. Furthermore, the execution of these tasks is typically siloed and inefficient resulting in wasted man hours and more time spent in the field collecting data.

Leveraging an ARA, facility leaders can see all of the failure modes and mechanisms for both the fixed and rotating components of the exchanger. Additionally, the ARA links the maintenance and inspection tasks needed to mitigate the failure modes. These links create the foundational data infrastructure to optimize using more complex analyses such as machine learning and artificial intelligence.

Benefits of an ARA

With ARAs, facilities can determine where they are wasting their reliability and maintenance budgets and can better identify where they can re-allocate their budgets. Additional benefits include:

  • Assess all asset types using the same methodology and quantitative results, breaking down siloes in reliability and enabling effective comparison and prioritization of risks and asset management plans across all asset classes
  • Clearly understand causal links between all asset functions, failure modes, failure mechanisms, critical reliability data, and field execution tasks, laying the foundational framework for any successful reliability program.
  • Create the framework to understand the benefit to cost of every task for all assets in your facility

To learn more about how an ARA fits into Quantitative Reliability Optimization (QRO), read about QRO here.

More resources like this