A methodology for calculating sample size to assess localized corrosion of process components

This paper proposes a methodology to estimate the required sample size to assess, with a specified precision, the localized corrosion of process components. The proposed methodology uses the extreme value and bootstrap methods. The results of estimated sample size ensure that the predicted maximum l...

Full description

Saved in:
Bibliographic Details
Published in:Journal of loss prevention in the process industries 2012, Vol.25 (1), p.70-80
Main Authors: Khalifa, Mohamed, Khan, Faisal, Haddara, Mahmoud
Format: Article
Language:English
Subjects:
Acceptability
Bootstrap
Bootstrap method
Confidence intervals
Corrosion
Errors
Extreme value method
Extreme values
Gumbel probability distribution
Inspection
Localized corrosion
Mathematical analysis
Methodology
Pipelines
Sample size
Standard deviation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper proposes a methodology to estimate the required sample size to assess, with a specified precision, the localized corrosion of process components. The proposed methodology uses the extreme value and bootstrap methods. The results of estimated sample size ensure that the predicted maximum localized corrosion with the extreme value method is within an acceptable margin of error at a specified confidence level. Using the results of the proposed methodology, an equation is introduced to calculate sample size as a function of the acceptable margin of error, the population size, the standard deviation of corrosion data and the required confidence level. The probability of exceedance of critical limit of localized corrosion is also estimated. The methodology is explained through a case study of localized corrosion in process piping. ► A new methodology to estimate the sample size to assess the localized corrosion. ► The methodology is built upon bootstrap sampling and the extreme value method. ► The developed methodology is tested and validated using a real life case study.
ISSN:0950-4230
1873-3352
DOI:10.1016/j.jlp.2011.07.004