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51315-5441-Refinery Piping Mechanical Integrity: Enhancing Assessments Using Statistical Tools

Picture for Refinery Piping Mechanical Integrity: Enhancing Assessments Using Statistical Tools
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Product Number: 51315-5441-SG
ISBN: 5441 2015 CP
Author: Douglas Milton
Publication Date: 2015
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$20.00
$20.00
Assessing the mechanical integrity of refinery piping circuits can be challenging. Reasons include lack of internal inspection capability presence of localized vs. uniform corrosion mechanisms variable corrosion rates over time potential for multiple damage mechanisms to be present variable age & quality of thickness data as well as the large volume of pipe to be inspected and the associated cost and logistics of carrying out extensive inspections. This paper will present examples of how statistical evaluation of piping thickness data has been used successfully to enhance assessments of the mechanical integrity of piping circuits in refinery process units. Applications examples include circuits in hydro processing units atmospheric and vacuum crude distillation units coker units. The paper will also explore how statistical concepts can help frame the approach to managing the challenge presented by low Silicon carbon steel.
Assessing the mechanical integrity of refinery piping circuits can be challenging. Reasons include lack of internal inspection capability presence of localized vs. uniform corrosion mechanisms variable corrosion rates over time potential for multiple damage mechanisms to be present variable age & quality of thickness data as well as the large volume of pipe to be inspected and the associated cost and logistics of carrying out extensive inspections. This paper will present examples of how statistical evaluation of piping thickness data has been used successfully to enhance assessments of the mechanical integrity of piping circuits in refinery process units. Applications examples include circuits in hydro processing units atmospheric and vacuum crude distillation units coker units. The paper will also explore how statistical concepts can help frame the approach to managing the challenge presented by low Silicon carbon steel.
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