Intertek will be presenting at the 2019 API Inspection and Mechanical Integrity Summit
30 Jan 2019
This four-day summit includes three days of presentations spanning over 120 topics. Each day focuses on presentations relevant to upstream, midstream, downstream operation and integrity management. API Inspection Summit provides an opportunity to hear about emerging trends from experts, and to discuss new and existing issues in inspection and AIM technology.
When: January 28, 2019 - January 31, 2019
Where: Galveston Island Convention Center, Galveston, Texas
Intertek Experts presents will be presenting:
Mobile Reporting and Tracking for Improved Pipeline Integrity Management
Rana Ghosh, Intertek
A big challenge in dealing with pipeline integrity is the lack of traceability of pipe sections and correlating inspection and ILI data. Pipelines are built with pipes from different mills in various locations across the globe. Providing pipeline owners the ability to capture and track high quality pipeline data through all phases, including manufacturing, construction and operation is required. Mobile field inspection and reporting management solution increases the overall productivity during the manufacturing and in-service phases by reducing the time to document inspections and streamlining the workflow. By combining traceability and inspection into one task, owners and operators achieve full transparency into the manufacturing process retain a digital record which is vital for assurance and compliance purposes and accessible anywhere in the world.
Phased Assay Detection and Metallurgical Analysis of Creep Fatigue Cracking
Terry Haigler, Intertek
Routine inspections coupled with a good condition-monitoring program are a critical part of the maintenance and safety of piping systems. The detection and field evaluations of indications using a nondestructive technique are only part of understanding the significance of the indications in your piping. Intertek AIM will present a case study of a routine inspection that leads to a significant indication and the steps taken to analyze and eliminate the indication. Detailed discussions will be given on the NDE processes used to evaluate the indications including magnetic particle inspections, encoded phased array inspections, hardness values, field replications, and positive material identification results. We will also discuss boat samples and the metallurgical analysis performed in the laboratory to further evaluate the root cause of the indications.
Predicting Dissimilar Metal Weld Failures using Machine Learning Techniques
Martin Gascon, Intertek
The increasing share of renewable energy production has resulted in new challenges for the operators of traditional power plants who are required to maintain high reliability and high profits. For example, operations must become flexible when dealing with the thermal strain and the wear-and-tear of operations. This is not unlike the challenges found in the petroleum refining industry. This study found a correlation between flexible operations and Dissimilar Metal Welds (DMW) failures. We tested different machine learning techniques and found that artificial neural networks is the best approach for analyzing these type of failures, exhibiting an overall prediction rate over 90%. This method can even reasonably estimate the time to failure.