Inspectioneering
Inspectioneering Journal

Cognitive Inspection Analytics in Asset Performance Management

Take intelligent actions from inspection data during a turnaround

By Vipin Nair, Senior Product Manager at GE Compliance and Integrity Management, and Sarah Lukens, Data Scientist at GE Digital. This article appears in the March/April 2018 issue of Inspectioneering Journal.
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Introduction

A turnaround, or TAR, is the period of time when a process plant is shut down for inspection, testing, maintenance and repair. The TAR cycle is primarily governed by inspection schedules mandated for pressure equipment by the regulatory bodies responsible for industrial safety and health norms in various geographical locations. Time is crucial during a TAR and requires significant up-front planning and resources to ensure certified inspectors complete the inspections on time and actions are taken against important asset findings.

Ultimately, inspectors aim to optimize analysis and recommendations during TAR to prevent unplanned downtime until the next scheduled TAR.

The asset data and information generated during a TAR, such as inspection reports, typically require weeks to analyze, extending the inspection process far beyond the TAR timeline. This delay in analysis could potentially miss the opportunity to mitigate a risk during the TAR window. This delayed analysis stems from various challenges, including consolidating data from contract inspectors, prioritizing assets that demand immediate attention, and reconciling isolated work processes that aren’t integrated, such as disconnected communications between the inspector, corrosion analyst and the risk analyst. While an inspection department might inspect all required pressure equipment and repair the visible degradations, it cannot confidently rely on the inspection report generated during the TAR until these challenges are mitigated and all data has been fully analyzed. Without detailed analysis, the inspection team faces a “risk of unknown” for a possible unplanned failure before the next TAR.

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