An energy company struggled with manually identifying thermal heaters’ schematic symbols within thousands of complex CAD schematics. This laborious process not only consumed hours of work but was also prone to human error, which negatively impacted inventory tracking and compliance documentation. As the volume of schematics increased, maintaining accuracy and efficiency in tag number extraction became extremely challenging.
To address these challenges, Rannsolve’s AI-powered Cognitive Data Extractor was implemented, which could automatically detect thermal heater symbols within high-resolution CAD schematics. By using advanced image recognition models, CDE identified the unique shapes of heater annotations and accurately extracted the tag numbers associated with them from the technical details around them. This automation solution not only drastically reduced the need for manual review but also increased precision in data extraction, allowing the company to process a large volume of CAD files with ease.
The AI-powered CDE automated indexing of over 25,000 schematics per month with an impressive >95% AI detection accuracy. Energy teams saved more than 70% of manual effort, which significantly improved engineering asset tracking and compliance documentation.
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