API RBI for HE Bundles
Many companies currently predict bundle life by analyzing the history of each heat exchanger bundle since the installation date of the bundle. The problem with this approach is that many exchangers may experience few, if any, bundle failures during an exchanger’s life, and some failures may not apply to current operating conditions or practices. In addition, this approach is not based on a statistically significant data set to make an accurate prediction of future performance or probability of failure for the heat exchanger bundle.
To facilitate a more accurate prediction of future performance, the API RBI methodology uses the combined experience of other heat exchanger bundles of similar design and in similar service so that a failure rate can be statistically analyzed. Consequences are based on financial losses due to lost production due to downtime associated with repair or replacement of the bundles.
To predict bundle probability of failure, the method utilizes a weibull distribution based on either the bundle’s inspection history (if enough failure history exists) or set of matching bundles from the failure library. Matching criteria to determine similar bundles include:
- Exchanger Type
- Tube Metallurgy
- Tubeside and Shellside Fluid Categories
- Operating Conditions, Temps, Pressures, Velocities, etc.
- Process Unit
- Controlling Damage Mechanism
- Fluid Damage Modifiers (H2S, Sulfur, Caustic, etc.)
- Many, many others
The failure rate curve is modified based on how much is known about the current condition of the bundle, in other words, uncertainty is added based on the effectiveness of the inspections conducted on the bundle to date. Inspection recommendations are made during the plan period to reduce the overall risk of bundle failure down to an acceptable value.
