Case study | Energy
Modernising Transformer Inspections with AI-Assisted Data Capture
Replacing manual evaluations with a digital inspection platform that automates data capture with AI-assisted OCR and maintains quality control through human oversight.
Overview
A leading electrical power and distribution provider relied on lengthy, manual transformer evaluations that slowed inspections and depended heavily on experienced personnel. 10Pearls developed a tablet-based evaluation solution that digitised inspections and significantly accelerated evaluation while improving consistency and accuracy.
in nameplate extraction
from days to ~1 hour
Challenge
The organisation needed a more efficient and accurate way to conduct transformer evaluations. Existing processes required multiple layers of testing, manual recordkeeping, and on-site involvement from experienced personnel. Evaluators frequently relied on experts to interpret equipment information. Documenting results manually created additional delays and inconsistencies throughout the evaluation process.
Solution
10Pearls created a tablet-based evaluation platform that digitised transformer inspection workflows. Evaluators could capture testing data directly on tablets, replacing manual documentation, and creating a standardised process for recording inspection findings.
The solution incorporated AI-assisted optical character recognition (OCR) technology to automatically extract information from complex transformer nameplates in approximately 30 seconds with roughly 94% accuracy. Inspection data collected in the field was then routed through an online review portal, enabling reviewers to validate results and maintain quality controls through human oversight at every stage of the evaluation process. The result was a faster, more scalable evaluation workflow that reduced reliance on manual processes while improving consistency and operational efficiency.
Top industrial transformer company
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