Inspection budgets keep growing, but it is difficult to defer inspections with certainty because there is a lingering feeling that the risk is high, so you err on the side of caution.
Many facilities still operate on fixed inspection cycles and qualitative risk models that apply the same prioritization logic to every asset, which drives unnecessary reviews and costs on low-value inspections. However, high-consequence risks can remain undetected until they result in unplanned downtime, safety incidents, or regulatory exposure.
What if you had the ability to have a comprehensive look at all your planned inspection areas that were based on data-based logic, quantified risk, and measurable business impact, that could definitively tell you what areas don’t need more inspections, and which areas should be added?
Quantitative Reliability Optimization (QRO) delivers inspection optimization based on your data that pinpoints Probability of Failure dates and the consequence of failure of every asset. When you have precise, real-time analysis at your fingertips, it enables you to make confident decisions to eliminate non-value work and focus resources where they deliver the highest return.
The Cost of Over-Inspection and Under-Inspection
Over-inspection consumes significant time and budget on assets that, when evaluated through a quantitative risk model, present little to no meaningful threat to production or safety. These inspections are conducted based on a fixed schedule. Rather than delivering measurable value, they tie up resources that could be addressing higher-priority work.
Under-inspection, on the other hand, occurs when degradation mechanisms (often internal, localized, or difficult to detect) are left unmonitored. Without a quantified Probability and Consequence of Failure, these hidden risks can escalate unnoticed until they result in production, HSE, and compliance consequences.
Traditional inspection programs are often limited by siloed data systems, inconsistent evaluation logic, and static, qualitative models that fail to account for uncertainty and lead to wasted spend on low-risk assets and missed opportunities to mitigate the most critical threats.
The QRO Inspection Optimization Process
QRO transforms inspection planning by combining proven engineering principles with advanced data science:
- Data Intake & Integration – QRO streamlines inspection history (including CML-level readings), process and lab data, predictive monitoring results, and industry failure models into the QRO engine called Newton™ that creates one connected reliability model.
- Risk Modeling – Newton™ calculates the Probability of Failure (POF) for each failure mode at the CML or mechanism level, and pairs it with a Consequence of Failure (COF) that factors in production losses, HSE risks, and repair/replacement costs.
- Scenario Analysis – Engineers can model multiple inspection strategies in just minutes to see the impact on cost, compliance, availability, and risk.
- Optimization Output – The model produces a prioritized inspection plan that identifies what can be deferred, added, and adjusted, ensuring each task delivers maximum risk reduction per inspection dollar while meeting compliance requirements.
Benefits Beyond Cost Savings
While cost reduction is a major advantage, inspection optimization with QRO delivers broader value:
- Improved Safety and Compliance – Inspection activities are aligned with the highest HSE risks, ensuring regulatory standards are met or exceeded.
- Increased Availability – High-priority risks are addressed before they can cause outages.
- Faster Planning Cycles – Optimized inspection plans are delivered in weeks instead of months, with updates as new data becomes available.
- Clear Business Alignment – Every inspection is tied to its measurable impact on availability, safety, and cost.
Proven Cost Reduction Without Added Risk
At a mid-size chemical plant on the U.S. Gulf Coast, an inspection optimization pilot project was run on one unit using QRO-based planning with a 10-year outlook for piping systems. The analysis identified the potential to defer 10,635 piping inspections without increasing risk. QRO analysis revealed an overfocus on internal corrosion monitoring and a need to increase monitoring for external corrosion, and recommended reallocating inspection resources where they had the most impact.
The optimized plan reduced CML inspections from 11,392 to just 757, lowering estimated inspection costs from $5,696,000 to $378,500. This translates to savings on the Ethylene Unit inspections of $5,317,500 and a projected annual value of $8,800,000 once QRO is deployed sitewide.
Additional benefits included:
- Inspection visibility extension from 10 years to 25 years for the analyzed systems.
- Identification of unmonitored, statistically probable risks to proactively mitigate potential leaks not previously monitored.
- Closing critical data gaps in reliability, reducing costly “clean-up” investigations after unplanned issues.
- Full API 580 & API 570 compliance through statistical, risk-based prioritization.
Cut Costs Without Risk with Pinnacle
Inspection optimization isn’t about reducing work, but rather about focusing inspection efforts where they deliver the highest value. By combining advanced reliability engineering, real-time data, and system-level modeling, QRO ensures every inspection dollar is spent where it has the greatest impact. With QRO, facilities can cut costs, improve safety, and boost availability without increasing operational risk.
Your inspection optimization can be leaner, smarter, and safer. Connect with Pinnacle today to learn how Quantitative Reliability Optimization can transform your inspection strategy.