Author: Lawrence I. Cleland, Senior Engineer I; Group Head
One of the definitions I found on Google for the word ‘uninspectable’ reads: “not inspectable; incapable of being inspected.” Now, that might not be the most attention-grabbing first sentence of an article you’ve ever read, but it’s a good place to start this discussion of an incredibly important and under-understood (?) risk-based inspection (RBI)concept known as Uninspectable Risk. It does not, as the name might misleadingly suggest, describe assets that are incapable of being inspected, nor does it describe a situation wherein an asset’s risk is incapable of being assessed. Instead, the term Uninspectable Risk refers to the idea that an asset’s Consequence of Failure (COF) is so tremendously high that the asset’s risk is unable to be suitably reduced through inspection alone. This is an incredibly important if seemingly pedantic distinction, because having an asset with Uninspectable Risk should never mean that regular, highly effective inspection is seen as superfluous and unnecessary; if anything, inspection is more necessary for an asset with extremely high COF since the danger of it failing is so great. But understanding this definition is the first step in developing a well-reasoned risk mitigation strategy for managing assets with Uninspectable Risk; one that ideally combines a deft navigation of advanced RBI concepts with, ironically, inspection.
“What is Risk?”, and other questions you might ask if you don’t know what RBI is
“What is Risk?”
Per API RP 580(1), risk is the product of two factors: Probability of Failure (POF) and Consequence of Failure (COF). Without diving into the minutia too much (download the in-depth RBI discussion for more information), it is critical to understand that POF increases over time and decreases with inspection, and that COF is a constant value based on the static operating conditions assigned to a particular asset. This simple mathematical relationship can then be logically followed to mean a few things:
- Any reduction in POF will reduce risk by a proportional amount,
- An outsized COF will require a very small POF in order to avoid an outsized risk, and thus,
- The need for large POF reductions through inspection is greater for larger values of COF.
Note: The following observations were developed from extensive use of the Level 2 COF model, as described in API RP 581(2), but the lessons learned should be universally applicable for any RBI methodology.
“How am I to know how much to reduce my risk? Surely it is acceptable for assets with a high COF to have a similarly high risk!”
The asker of this clunky question might be surprised to learn that their assumption is incorrect. RBI utilizes a maximum acceptable risk threshold known as a risk target. This risk target is typically set at a risk value that generally corresponds to what could be thought of as being a “reasonably acceptable risk.” So as an asset’s POF increases over time through its steady degradation caused by its various active damage mechanisms, RBI recommends that an inspection is performed once the risk rises to exceed this risk target. The quality and extent of that inspection will directly influence the amount of POF reduction (and thus proportional risk reduction) that occurs, which is hopefully enough to bring the asset’s risk under the risk target, at which point it will no longer call for inspection.
However, assets with larger COF values require proportionally larger amounts of risk reduction to fall under the risk target than assets with smaller COF values (assuming they have the same POF), which necessitates more prudent, targeted, and regular inspection. This can be reasonably, easily managed up to a point; it is only when an asset’s COF could be eloquently deemed ‘ultra-high’ that this balance starts to become unnavigable.
“How much COF would be considered ultra-high?”
This is a difficult question to answer in a quick, straightforward manner, because it relies so heavily on the owner-user’s risk tolerance. As previously mentioned, a risk target is typically set at a risk value that generally corresponds to a reasonably acceptable level of risk (the diagonal lines in the diagram above). Companies with higher risk targets can tolerate higher levels of COF, and thus their assets can be maintained with POF reduction through inspection more easily than companies with lower risk targets. Visualizing this relationship is easier using a risk matrix, which is a chart that plots POF vs. COF, allowing for risk targets to again be depicted as diagonally decreasing lines, since risk is the product of POF and COF. Below is the example unbalanced 5×5 risk matrix depicted in API RP 581(2), modified to include a risk target line:
When an asset’s POF rises to the point that its risk exceeds the risk target, an inspection is required, which should reduce the risk to a tolerable level. Using the example risk target above, you can see that a hypothetical asset that exceeds the risk target in the bottom-right cell already has a near-zero POF; it is not a safe assumption that it will always be possible to achieve the goal of reducing the risk below the risk target for an asset that is considered “high risk” with a POF that low. Fortunately, while such ultra-high COF assets do exist, they account for only a small fraction of equipment in a given processing facility.
The Risk Matrix Revisited
With that understanding of risk targets, POF reduction, and ultra-high COF, we can focus on the bottom-right cell of the risk matrix to visualize some clear examples of Uninspectable Risk. The risk matrix to the right has been further modified from the previous example to include two plotted points representing assets, one of which has a risk that is able to be maintained through inspection (and is thus able to fall below the risk target) and the other of which has a risk that is not able to do the same (with the assumption that we are not reasonably able to reduce its POF any lower than it is already – assume it is an older asset that has undergone some amount of degradation in the past).
The example risk matrix above illustrates a simple assumption that can be used to make a quick educated guess as to whether an asset has Uninspectable Risk: a very high COF coupled with a very low POF, relative to the risk target. This also helps demonstrate the value of properly setting a risk target, because a risk target set higher than both data points would inherently mean that neither asset would have Uninspectable Risk.
However, there is one major issue with viewing a risk matrix in this way: COF does not technically have an upper limit. The example risk matrix above may show a COF that cuts off at 1,000,000 ft2/92,903 m2, but COF may be higher than that. The reimagined risk matrix below showcases (very elegantly) just how high COF can be, relative to the risk target, and helps illustrate how expansive the fifth column of the example risk matrix truly is:
The main thing this expanded view emphasizes is that regardless of what specific risk target is being used in the RBI assessment, there will come a point where the COF is so high that there is no possible way to reduce risk below the risk target. This is why Uninspectable Risk is such a complicated issue – if the point of RBI is to restructure an asset’s inspection schedule to be as efficient and targeted as possible, then how do you perform RBI on an asset that will alwaysrequire an inspection?
To inspect or not to inspect?
Uninspectable Risk presents the following “impossible” question to RBI users: do I continue to inspect my ultra-high COF assets with little resulting risk reduction, or do I find a more creative solution to the problem? Ultimately, this question is concerned with whether there is value in treating all assets in RBI consistently, or whether RBI should be used in different ways for different assets – something that could be a slippery slope if faced with other undesirable inspection recommendations in future. Before that question can be adequately answered, however, we should first consider a few other potential risk mitigation strategies besides inspection.
As previously established, COF is a constant value. The particular variables that go into determining an asset’s COF may differ slightly from one RBI methodology to another, but they generally include some combination of the following: the static modeled operating conditions and fluid of the asset, the mass and volume of the fluid within the asset, the mass and volume of the fluids within any associated assets in the process inventory group, the possible failure event outcomes for the considered asset, and the available process systems in place that may be able to reduce the resulting COF if a failure were to occur. Validating the accuracy of these variables should be the starting point for any RBI user encountering an asset with Uninspectable Risk.
After doing so, if the asset still has Uninspectable Risk, the only remaining considerations involve changing the risk criteria on a case-by-case basis, thus introducing an inconsistency in the application of a user’s RBI program. It is highly recommended to document any such adjustments in the user’s RBI manual, so as to explain the technical basis behind the decision as well as to allow future users to replicate that decision if needed.
The first solution likely to be considered is changing the set risk target for any assets with Uninspectable Risk. This would essentially mean that these assets are not being compared to the same “acceptable day-to-day” risk threshold as the other assets in the RBI program, but rather to a higher one-off risk threshold specifically intended to capture ultra-high COF assets. The practical meaning of this risk target increase is that the user would be stating their willingness to accept more risk from their ultra-high COF assets. How high to set this adjusted risk target is a decision that will require some careful consideration, but it should reflect an allowance for the POF to continue to rise over an amount of time that would thread the needle of requiring regular inspection without being overly excessive before hitting the risk target again (say, approximately every 6 months – 1 year, for instance).
Another option would be introducing a reduced maximum inspection interval, which is a time-based inspection recommendation target typically used to ensure that low-risk assets do not inadvertently go more than 25 years without being inspected in some form. Setting this target at a very low value for ultra-high COF assets would be a way to establish inspection at more strictly fixed time-based intervals, without resorting to removing the assets from RBI altogether. This could also be achieved by setting a low Damage Factor Target (or POF Target) for this particular asset, in order to manage its inspection solely based on Damage Factor (or POF).
Relatively Relative
Some users might be deterred by such one-off approaches, however. RBI’s efficacy heavily relies on its ability to consider relative risk between assets, as opposed to absolute risk; this distinction means that it is more important to be consistent within an RBI program than to have every input value captured perfectly correctly (in other words, precision is valued over accuracy). Once a user starts modifying RBI risk criteria on a one-off basis, this consistency has vanished. And since increasing the risk target for all assets would negatively impact the regularly recommended inspection of low COF assets as well, that is not necessarily a good solution either.
A more recently adopted approach is to use a maximum COF area option, by which any COF above a certain amount (say, 100,000 ft2/9290.3 m2, for example) is automatically reduced to that set amount in the risk equation. This effectively equates all ultra-high COF assets in their proximal relation to the risk target so that the only remaining comparative metric is POF. Of course, this also means that there is a significant amount of blurring of ultra-high COF values, where an acid settler and a butane sphere, for instance, would have the exact same COF. However, inspection will still be recommended regularly enough that this option may be the simplest and most effective solution to Uninspectable Risk.
The risk matrix below has been further modified to add a maximum COF area option of 100,000 ft2/9290.3 m2, whereby all ultra-high COF assets are capped at that value and are thus shifted to the left of their original positions on the previous risk matrix. Doing so means their risk values are all capable of being reduced below the risk target through inspection; in other words, they no longer have Uninspectable Risk.
Regardless of which approach makes the most sense for each user, the important thing to emphasize is that there is not necessarily one perfect solution for managing assets with ultra-high COF and Uninspectable Risk. If any of these more technocratic solutions is deemed overly complicated or needlessly overthought, there is always the option of simply removing any ultra-high COF assets from RBI altogether and then managing their inspection through the prescriptive time-based inspection approaches of API 510, 570, and 653. Alternatively, a user could inspect their ultra-high COF assets every chance they get, in order to reduce the POF to as low as reasonably practicable (ALARP) but without having the inspection dates governed by various RBI risk criteria.
Conclusion
Uninspectable Risk is a complicated and poorly understood RBI concept, but it is not rarely encountered. Having a well-considered strategy in place to counter Uninspectable Risk will go a long way in improving any user’s RBI implementation and may ultimately reduce unnecessary inspection. While several potential solutions to the issue exist, none is perfect, and it is ultimately the user’s responsibility not only to select the one that works best for them, but above all, to document that choice in their RBI manual so the decision is transparent, repeatable, and consistent.
If you have any questions regarding Uninspectable Risk or ultra-high COF, please fill in the form below.
References
- API, API RP 580 Recommended Practice for Risk-Based Inspection, American Petroleum Institute, Washington, D.C.
- API, API RP 581 API RBI Methodology, American Petroleum Institute, Washington, D.C.