What is Quantitative Reliability Optimization (QRO)?
QRO is an evolution in reliability modeling that combines the best traditional methods, data science, and subject matter expertise to help you make confident business decisions.
Reduce Your Uncertainty with Quantitative Reliability Optimization (QRO)
Quantitative Reliability Optimization (QRO) is a methodology that evaluates the impact of individual assets on the overall performance of a system by connecting reliability and integrity data to a system model. QRO aids facility personnel in making informed decisions by quantitatively measuring the impact of each reliability action against the cost, risk, and production of the entire system.
Identify the tasks that actually impact your facility’s performance.
Regardless of how mature your reliability program is, having the ability to quantify the uncertainty of your facility’s data will help you identify the tangible actions that will have the greatest impact on your facility’s performance.
The industry's approach to risk management has evolved.
Just as time-based and risk-based approaches were revolutionary when introduced, QRO is the next evolution of reliability modeling. QRO quantifies the impact of specific tasks on an asset’s probability of failure, equipping facilities with the information they need to reduce uncertainty and make reliable decisions.
Time-Based
Requires minimal data
Leverages static data that does not connect to other systems
Results in siloed strategies that provide minimal insight into overall risk
Yields minimal ROI
Risk-Based
Requires a moderate amount of data
Leverages static data that does not connect to other systems
Results in a robust, risk-driven program, but overall value is limited due to siloed nature of data
Yields moderate ROI
QRO
Requires a moderate amount of data
Leverages live data connection between systems
Enables interconnected strategies that provide holistic insight into overall facility risk
Yields greatest ROI
How QRO Unlocks Data-Driven Insights
To fully leverage data-driven insights, facilities need to evolve their use of reliability intelligence. QRO creates a comprehensive view of a facility’s reliability by quantifying the uncertainty of individual assets and using that information to construct a system model.
Asset Risk Analysis (ARA)
Integrates loss of containment risk with loss of function to create an asset centric analysis.
Lifetime Variability Curve (LVC)
Predicts failure using data science principles that update dynamically as new data enters the system.
Forecasting System Availability
Models how each asset, component, or data point impacts facility performance.
Reliability Simulation and Performance Optimization
Identify plans for the highest performance at the lowest cost while ensuring operational safety.
Creating a Common Reliability Language Across Your Facility with QRO
Whether you’re an operator, plant manager, or executive, every role has an impact on your facility. QRO creates a common reliability language across your entire facility by creating a system view of your asset’s health that helps you justify the value of your actions/plan.
Field Personnel
Understand how the data you collect connects to the overall objectives of your facility.
Management
Have confidence that your team’s tasks will impact your reliability goals.
Executive
Meet your organization’s goals by having a clearer picture into financial and availability planning.
QRO Case Studies
Learn how two facilities with programs at varying levels of maturity successfully leveraged QRO to model failure degradation, forecast availability with limited data, and justify capital expenditures.
Model Failure Degradation
A large energy producer simulated thinning and vibration scenarios through QRO to quantify future risk and visualize the potential impact these scenarios have on the facility’s future availability and costs.
Despite having limited data, a global energy producer was able to forecast the future availability of one of its critical units and drive quantified, data-driven decisions through QRO.