Manufacturing
Manufacturing Process Automation with AI Quality Control
Client: Automotive Component ManufacturerDuration: 10 monthsTeam Size: 16 engineers
50%
Defect Reduction
70%
Downtime Reduction
100%
Line Speed QC
$4.8M
Annual Savings
The Challenge
What We Were Asked to Solve
The client's manual quality inspection process was a bottleneck causing 8% defect escape rate to customers. Three shifts of QC inspectors examined parts at 40% line speed. Annual recall costs exceeded $5M. Machine downtime was unpredictable, with 15% of production time lost to reactive maintenance.
Our Solution
How We Solved It
Deployed computer vision cameras with custom defect detection AI, real-time IoT sensor network monitoring machine health, predictive maintenance ML models analyzing vibration and temperature patterns, and integration with existing SAP ERP for automated work order creation on predicted failures.
Impact Delivered
Key Outcomes
Defect escape rate reduced from 8% to 0.4%
Production line speed increased by 40% with automated QC
Unplanned machine downtime reduced by 70%
Predictive maintenance catching 95% of failures 2-4 weeks in advance
QC inspector team redeployed to process improvement roles
Technologies Used
PythonTensorFlowOpenCVAzure IoTInfluxDBPower BISAP
“
The AI quality control system sees defects the human eye cannot catch. Our defect rate is now best-in-class for our industry.
Michael Zhang
VP Manufacturing Operations
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