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 the existing first principle’s reliability models with new data science, multi-variate analysis, and system-based optimization. This combination improves 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.
ARAs integrate industry-leading engineering principles, field execution tasks, and measured data to quantify uncertainty and optimize all tasks and spending at a facility. ARAs create a causal link between assets’ functions, failure modes, and failure mechanisms to identify the reliability and maintenance tasks needed to mitigate failures and reduce uncertainty. As a result, you will be better able to streamline the deployment of limited resources and help facilities achieve a strong return on investment.
Typical reliability methodologies measure various 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. ARAs are driven by critical reliability data, giving you better insight into the failure risk of their assets and enabling them to shift to a more proactive approach to reliability and maintenance.
By evaluating assets consistently and quantitatively in a single platform, facility leaders can now effectively compare risks or prioritize resources across different asset classes.