/case-studies / manufacturing-vision-quality
DATA & PREDICTIVE AI

Computer-vision quality inspection for a manufacturer

client
Electronics Manufacturer
industry
Manufacturing
services
AI / ML · Edge
duration
6 months
fig.80// skillikzmodeltraininfervectorAImodel.evalrollout88%98%accuracyusage90coveragelive
// OVERVIEW

Electronics Manufacturer — a manufacturing organisation — engaged Skillikz on vision quality inspection: Automated defect detection on the production line. This case study sets out the business challenge, the AI-led approach we took, the technologies involved and the measurable outcomes delivered over 6 months.

// TECHNOLOGIES
PythonPyTorch / scikit-learnMLflowSparkAWS SageMaker
defect detection
-40%
escapes
real-time
on the line
edge
inference
01 // THE CHALLENGE

Manual visual inspection missed defects under speed and fatigue, letting faults escape to customers.

02 // OUR APPROACH

We deployed computer-vision models at the edge to inspect every unit in real time, flagging defects for action.

Vision models trained on defect imagery
Edge inference on the production line
Operator alerts and feedback loop
Continuous retraining and monitoring
03 // THE RESULTS

Defect detection improved and escapes fell 40%, with every unit inspected in real time on the line.

Every unit gets a perfect, tireless inspector now. Quality complaints dropped sharply.

Quality Director · Electronics Manufacturer
// HOW WE'D DELIVER THIS TODAY

The AI services behind this outcome

A project like this draws on a focused set of Skillikz services — from first assessment to a working pilot and a clear path to scale.

// MORE WORK
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