What is Quantitative Reliability Optimization (QRO) and Why Should You Care?
A changing world economy is challenging industries worldwide, and as a result, it forces owner-operators to become more efficient. Reliability plays a large part in facility efficiency. Industry reports indicate there are three things that companies can do to improve operating margins: 1) Run the facility more efficiently, minimizing energy costs while maximizing the value of the product mix, 2) Run the facility more frequently, with a lower ratio of downtime, and 3) Lower costs associated with maintenance, repairs, turnarounds, personnel, equipment, etc. The last two of these items are directly impacted by reliability. According to one , it is estimate that global refiners spend more than $50 billion annually on reliability-focused activities with between 10% and 30% of this spend is wasted, not improving reliability. One of the significant challenges is identifying the waste, knowing how to eliminate waste safely or where you can reallocate those wasted resources to yield more value, such as shifting to proactive and predictive maintenance strategies. Not just remove or reallocate using traditional means today but to do that with quantitative confidence.
Quantitative Reliability Optimization (QRO) is an evolution in modeling that brings the best traditional reliability methods, multivariate machine learning, and subject matter expertise into one hybrid model, which seeks to maximize facility reliability and performance. This methodology balances commonly conflicting metrics such as production targets, HSE risks, and reliability and maintenance costs. By evolving and integrating reliability programs that are being used in the industry today like Risked Based Inspection (RBI), Reliability Centered Maintenance (RCM), Reliability and Maintainability (RAM) Modeling, Spare Parts Optimization, and Process Hazards Analysis (PHA). QRO seeks to elevate the way reliability is done. Over the last several decades, a variety of reliability programs have been implemented worldwide that were very well-intentioned and designed to solve specific problems at the time. These programs have resulted in improving reliability over the years; however, they have reached a place of stagnation. With that in mind, QRO was designed to optimize and evolve each step of the data-driven reliability framework to reach that next level of performance.
The Value of Quantitative Reliability Optimization (QRO)
We hear questions from around the industry such as, “where do I allocate my budget to get the greatest return,” or “how do I make more strategic decisions when I do not know how to focus my resources?”
Watch William Minter, President at Pinnacle, talk about how a global refiner implemented a QRO pilot at one of its facilities and was able to obtain the following results:
Watch William Minter, President at Pinnacle, talk about how a global refiner implemented a QRO pilot at one of its facilities and was able to obtain the following results:
Validate previous reliability spend
Calculate data-driven availability and predict future availability
Identify new inspection and maintenance tasks through task optimization
Prioritize new and existing maintenance tasks while also removing non-value-added activities based on identifying value and ensuring the highest return on investment
As the world’s largest industries place an even more considerable emphasis on lowering costs while sustaining operations, companies strive to ensure that reliability and maintenance investments are in the right places and result in increased performance. QRO brings value by tying everything together – cause and effect relationships from every data point and task to the impact on the facility reliability — with this link established, the model can then optimize and simulate to get the highest ROI. With that information, facilities can prioritize inspection and maintenance activities and make strategic decisions about replacements and upgrades with an associated return on investment value. By running scenario simulations for different maintenance and repair activities, QRO enables facilities to confidently forecast baseline and future availability. QRO empowers facilities to:
Economically justify reliability spend
Forecast facility availability and prioritize future bad actors
Model complex reliability scenarios for informed decision making
Provide a common reliability language
Drive facility sustainability
Better leverage data and expertise
Optimize availability, HSE risk level, and maintenance spend
Learn more about how QRO is helping facilities achieve the balance between maximized operating time and the investment to gain that run time.