What is Quantitative Reliability Optimization (QRO)?

Quantitative Reliability Optimization (QRO) empowers leaders at industrial facilities to make better reliability decisions. QRO is an evolution in modeling that combines the best traditional reliability methods, multi-variant machine learning, and subject matter expertise into a hybrid model. This model combines the risk assessments of both fixed and non-fixed assets, enabling leaders with the information they need to maximize facility reliability and performance. Just as RBI and RCM were major advancements for reliability, QRO is the next advancement of reliability modeling. QRO will enable you to better leverage your data to drive your decisions by helping you determine your facility’s current performance, identify your facility’s highest risks, and pinpoint major cost drivers.

What Quantitative Reliability Optimization Empowers You To Do

Economically Justify All Reliability Plans:

Understand the economic value of every maintenance, inspection, or reliability focused redesign at your facility

Model Complex Reliability Scenarios:

Optimize your reliability plans based on new design, different feedstock, pushed turnarounds, or market shifts

Drive Facility Sustainability:

Understand the spend and planning required to sustain a reliable, safe, and environmentally friendly facility

More Clearly Drive Digital Transformation:

Understand the data that is truly valuable to reliability and process safety and tap into and model off of that data

Provide a Common Reliability Language:

Empower your team to collaborate with safety, operations, finance, and management to create value-driven reliability plans

Better Leverage Expertise:

Use data to drive reliability decisions while focusing expertise on model refinement or reducing data uncertainty

Why Our Customers are Excited about QRO

With QRO, you can make quantified, data-driven decisions – even with limited historical asset data. We completed a QRO pilot for a global refiner and were able to build an accurate reliability prediction model for all of its assets despite having limited data. Listen below to learn why our customers are excited about QRO.

Case Study Highlight

How QRO’s Holistic Approach to Reliability Helped a Refiner Forecast Availability with Limited Data

A refinery recently implemented RBI, RCM, and real-time monitoring, but remained uncertain that they were investing in the correct places. Learn how we helped this facility ensure its reliability investments were properly focused to maximize availability and minimize risk with QRO

Unique Components of QRO

How QRO Works

Quantitative Reliability Optimization (QRO) is a dynamic reliability analysis model that synthesizes and expands upon the best elements of other existing reliability models while introducing new data science and analytical concepts to drive improved and strategically balanced availability, process safety, and spending performance.

Asset Risk Analysis (ARA)

An Asset Risk Analysis, or an ARA, integrates first principles engineering analysis and asset data with field execution limitations and operational constraints to build the foundation or our reliability operating basis.

Lifetime Variability Curve (LVC)

Lifetime Variability Curve, or an LVC, quantifies predicted failure using data science principles, leverages historical information or no data, and updates dynamically as new data enters the system, resulting in a more realistic and dynamic end of life prediction

Forecasting System Availability

Forecasting System Availability creates a dynamic cause and effect link between every data point and the facility, allowing operators to model how each asset, component, or data point impacts facility performance

Reliability Simulation and Performance Optimization

Reliability Simulation and Performance Optimization uses the causal links created, to simulate events and identify optimized plans to drive the highest performance at the lowest cost, while ensuring operational safety

How QRO Works

How QRO Works

Quantitative Reliability Optimization (QRO) is a dynamic reliability analysis model that synthesizes and expands upon the best elements of other existing reliability models while introducing new data science and analytical concepts to drive improved and strategically balanced availability, process safety, and spending performance.

Asset Risk Analysis (ARA)

Asset Risk Analysis (ARA)

An Asset Risk Analysis, or an ARA, integrates first principles engineering analysis and asset data with field execution limitations and operational constraints to build the foundation or our reliability operating basis.

Lifetime Variability Curve (LVC)

Lifetime Variability Curve (LVC)

Lifetime Variability Curve, or an LVC, quantifies predicted failure using data science principles, leverages historical information or no data, and updates dynamically as new data enters the system, resulting in a more realistic and dynamic end of life prediction
Forecasting System Availability

Forecasting System Availability

Forecasting System Availability creates a dynamic cause and effect link between every data point and the facility, allowing operators to model how each asset, component, or data point impacts facility performance

Reliability Simulation and Performance Optimization

Reliability Simulation and Performance Optimization

Reliability Simulation and Performance Optimization uses the causal links created, to simulate events and identify optimized plans to drive the highest performance at the lowest cost, while ensuring operational safety

Reliability Model Comparison

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Resources

Learn More About QRO

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