How Image Analytics Reduced Data Capture Costs by 90% and Inspection Time by 50% for Two Operators
If not properly identified and managed, corrosion can have a catastrophic impact on a facility. To mitigate the cost of asset failure and downtime that can result from corrosion, facilities must adopt a robust, proactive approach to corrosion assessment and mitigation. However, proactive corrosion management requires a sizable amount of data collection, processing, and interpretation, and many facilities struggle to allocate the budget and resources needed for this approach.
In this article, we discuss two use cases of how advanced visual data capture and image analytics can be used by multiple industries to drive better reliability decisions:
Coating Optimization for the Upstream Industry: An image analytics study for an upstream operator projects that new 360° cameras reduce the cost and time to capture and process corrosion data by 90%, to optimize coating programs.
Systematic Identification of External Corrosion in Midstream and Downstream Industries: An image analytics proof of concept (POC) showed that a machine learning model could be trained to detect external corrosion more systematically and reduce inspection time by 50%. Additionally, this model minimizes human subjectivity in inspections and creates consistency in both coating and inspection grading.
Watch as Sid discusses how recent advancements in visual data capture and image analytics are proving to be effective tools in helping facilities upgrade their approach to corrosion management.
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