ManufacturingEurope8-12 weeks
Predictive Quality Control System
10 weeks
IoT Lead + 2 ML Engineers
1The Challenge
Quality defects discovered late in production causing expensive rework. Manual inspection couldn't scale with increased production volumes.
2Our Solution
Deployed sensor-based quality monitoring with ML models predicting defects before they occur.
Approach
- Integrated sensor data from production lines
- Built real-time quality scoring models
- Created early warning alerts for quality drift
- Deployed dashboards for quality engineers
3Results & Impact
60% reduction in defect rate
£2M+ annual savings in rework
Quality issues caught 4 hours earlier on average
Inspection efficiency improved 40%
Key Takeaways
- Domain expertise from quality engineers was essential
- Sensor data quality was the biggest initial challenge
- Simple threshold models provided value before ML
Technology Stack
AWS IoTSnowflakeSageMakerGrafana
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