Why new RBI?

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Here we start a new series of posts which explain what exactly is offered by our new generation Plant Integrity Management strategy and tactics. Please don’t hesitate to communicate your thoughts or give us a like on LinkedIn.

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Risk Based Inspection planning (RBI) is on the scene for decades. Its rightful concept of proportioning integrity budgets to failure risks is a great common-sense solution for cost optimization.

The ever increasing budget savings pressure highlighted one major inability of the published RBI methodologies though. Financial management of industrial plants has set a question, which integrity management personnel can’t reply: ‘How much budget saving results from integrity management costs?‘ What happens is that both parties – integrity responsible and finance responsible – are striving to adopt a correct decision, but they are unable to communicate in a common language, as the current integrity management methods can’t enable a cost/benefit analysis with reference to integrity spending options.

For example, you are facing a choice of which inspection tools to deploy on a pressure vessel and over what surface area of this vessel. Failure of that vessel will shutdown the whole plant. Costs of a thorough inspection can be significantly higher than isolated spot checks, and the option choice proceeds as follows:

  1. Imagine, you have decided to inspect more thoroughly for an added safety. And then, a management approval is sought. As only the inspection costs are known and can be compared, but not the long term financial results and safety implications numerically, the cheapest option wins. The management simply does its best, as an ‘added safety’ is being qualified but not quantified.
  2. The winning cheapest option, in turn, may formally state that the vessel can be operated for another turnaround term, but there is not much confidence as the damage area coverage was only fragmentary, although inexpensive. But more importantly, the data analysis was not even performed to a level where remnant lives can be quantified, because an added cost of advanced analysis was also qualified, but not quantified regarding its outcome. It’s a closed loop.

The actual issue is with the RBI methodologies themselves, as there is no certain outcome of failure risks in dollars or victims versus time units. Regardless of which inspection tools were applied or not, neither Semi-Q RBI nor API RBI nor DNVGL RBI can prove plotting an actual curve of dollar or safety exposure risk projected in the future. This goal simply wasn’t set in these methodologies, as they were created in other decision making environments. Is the cost pressure good or bad – it doesn’t mater, as it is a part of the challenge we have to to combat. Or the challenge will combat us.

Now, a good explanation of what we promote needs a comparison. Eventually, it turned out that the wide engineering society tends to compare our method to API-581, as similar wording is used here and there. Our damage assessment and prediction model is substantially different to API. Please follow a corrosion example:

Plotting failure risks versus time can be attempted with the API-581 methodology, but the number of user choice factors will produce substantially different numbers for the equipment remnant life depending on the choice of those factors (such as inspection effectiveness and so on). The question emerges: which of the possible remnant life predictions is correct? Or closer to the reality than others? Or is there any prediction close to the reality?

Being practically involved with this uncertainty, we have developed a new integrity assessment method CoRBI®, which stands for Cost-of-Risk Based Inspection (and maintenance) planning.

CoRBI is a fully probabilistic assessment method, which uses practically no factors, hence, produces ONE result for one set of input data. Also, it indicates where the inspection data is not statistically representative, thereby offering inspection tools and coverage recommendations.

Next figure shows the Probability of Failure (PoF) predictions we have  obtained from example input data, in order to compare CoRBI and API-581 methods. This example uses actual internal corrosion data from multiple spot-check locations on pressure piping, which is statistically treated in CoRBI prior to the analysis. API-581 uses a single (worst case) corrosion depth value in contrast.

PoF graphs

It appears that the remnant life prediction changed drastically from API-581 2nd to 3rd edition (edition change occurred in 2016). CoRBI produces more optimistic results compared to the latest edition of API-581. Please also recall, that there are many more curves which can be achieved from API-581 by varying its user choice factors, while CoRBI produced only one curve relevant to multiple data points ‘as measured’.

We believe that the CoRBI PoF curve shape is better consistent with the damage physics, as the transition from negligible to significant failure probabilities occurs gradually over years, as opposed to API-581 derived curves, where a sharp PoF rise occurs within months at a certain age, why? The latter is most likely due to mentioned factoring of input data, and due to reducing the number of data points to a single ‘worst case’, hence to a single deterministic remnant life case.

This is said not to criticize the API route, but to offer a development over it. Indeed, a 20 years passed since the first API-581 was published.

The CoRBI PoF curve position is also consistent with the API-581 options, and also with industry professionals’ opinions and best experience. A series of experiments would ideally be required to get a numeric validation of PoFs, if this will ever be feasible.

In view of the CoRBI capability to treat any numeric data on integrity condition (for example crack length, valve time-to-failure, and more), we see it as a NEW RBI AND MORE. This is a complete novel Integrity Management Strategy, which is based on engineering science and on the actual integrity data. As a result, it does quantify integrity risks and predicts them in terms of fatality and dollar risk simultaneously. It replies the above cost/benefit question and promotes informed decision making, as well as harmonizes the interaction of financial and integrity teams.

The challenge was taken, and it’s now up to the plant owners-operators whether these new frontiers will be opened or the RBI approach will be conserved as it is, together with its neighbor problems such as NDT planning, stress simulation, design life calculations, which all now appear getting abandoned gradually, due to the said cost pressure.

So far, we studied only a limited number of examples from the Oil&Gas industry, and will be glad to get more data from more industries to see and offer all capabilities of our novel integrity assessment method.

If you want to know more, simply get in touch with us.

Next posts will illustrate some additional benefits we have facilitated along this R&D journey.

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