Fitness for Service (FFS) is a well known and important concept in the oil & gas, chemical, petrochemical, and other process industries. Fitness for service is the ability to demonstrate the structural integrity of an in-service component even though it contains a flaw. It serves as a rational basis for defining flaw acceptance limits, and allows engineers to distinguish between benign and dangerous flaws.
The FFS of any particular material is determined by performing a fitness for service assessment. Performing accurate FFS evaluations is an integral aspect of fixed equipment asset integrity management. On the other hand, failing to perform evaluations can lead to equipment failures which can further result in injury, loss of life, and severe financial and economic consequences.
The reason these examinations are performed is because even if a piece of equipment has a crack or other defect, this doesn’t necessarily mean that it’s unfit for service. Most equipment can continue in service despite small flaws, and to repair or replace equipment that can still be used would be an unnecessary and costly expense. Not only that, but unnecessary weld repairs can actually do more harm than good, as the quality of the new weld can often be less than the original one.
There are several ways to see if a flaw can cause a piece of equipment to be no longer fit for service. For cracks, fracture mechanics provides the mathematical framework for the examination by quantifying combinations of stress, flaw size, and fracture toughness.
While cracks tend to be the most dangerous, they’re not the only flaw that might warrant evaluation. Volumetric flaws such as corrosion pits, porosity, and slag may reduce the load-bearing capacity of a structure. Likewise, structural integrity may also be compromised by locally thinned areas which come grinding out cracks, thus FFS methodologies have been developed to evaluate local thinning. In these cases, acceptance criteria are based on limit load analyses rather than fracture mechanics models. Some examples of these different FFS methodologies are the BS 7910 method, API RP 579-1/ASME FFS-1 method, and the MPC/AP method.
It is important to note though that FFS evaluation can’t provide an absolute delineation between safe and unsafe operating conditions. Uncertainties in input parameters such as stress, flaw size, and toughness often lead to a large uncertainty in the prediction of the critical conditions for failure. In general there are two ways to address this uncertainty. The more traditional approach has been to use conservative input values in a deterministic analysis. The result of such an analysis is a pessimistic prediction of critical flaw size or remaining life.
An alternative approach, one which is becoming more common, entails performing a probabilistic analysis that incorporates the uncertainties in the input data. The latter type of analysis does not result in an absolute yes/no answer as to whether or not a structure is safe for continued operation. Rather, a probabilistic analysis estimates the relative likelihood of failure, given all of the incorporated uncertainties. Probabilistic FFS analysis can be an integral part of a risk-based inspection (RBI) protocol, where inspection is prioritized according to the risk of significant injury or economic loss.
Source:
https://inspectioneering.com/tag/fitness+for+service
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