Title

Statistical Methods for Estimating the Minimum Thickness Along a Pipeline

Campus Units

Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

5-2015

Journal or Book Title

Technometrics

Volume

57

Issue

2

First Page

164

Last Page

179

DOI

10.1080/00401706.2014.915236

Abstract

Pipeline integrity is important because leaks can result in serious economic or environmental losses. Inspection information from a sample of locations along the pipeline can be used to estimate corrosion levels. The traditional parametric model method for this problem is to estimate parameters of a specified corrosion distribution and then to use these parameters to estimate the minimum thickness in a pipeline. Inferences using this method are, however, highly sensitive to the distributional assumption. Extreme value modeling provides a more robust method of estimation if a sufficient amount of data is available. For example, the block-minima method produces a more robust method to estimate the minimum thickness in a pipeline. To use the block-minima method, however, one must carefully choose the size of the blocks to be used in the analysis. In this article, we use simulation to compare the properties of different models for estimating minimum pipeline thickness, investigate the effect of using different size blocks, and illustrate the methods using pipeline inspection data.

Comments

This is an Accepted Manuscript of an article published by Taylor & Francis as Liu, Shiyao, and William Q. Meeker. "Statistical methods for estimating the minimum thickness along a pipeline." Technometrics 57, no. 2 (2015): 164-179. DOI: 10.1080/00401706.2014.915236. Posted with permission.

Copyright Owner

American Statistical Association and the American Society for Quality

Language

en

File Format

application/pdf

Published Version

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