The Challenge
- Identifying defect parts in plastic profile manufacturing is a painstaking but necessary procedure for the client. Defects occur in various forms and due to various causes because of the complexity of the manufacturing process.
The Approach
- A machine learning – based quality prediction system
- Sensor-based process monitoring in pilot line
- Pilot line with iOT gateways and cloud connection
- Integration of crucial data from MES that was previously unused
- Initial business case (2 weeks)
- Prototype (2 months)
- Implementation (6 months)
- Subsequent roll-out to other production lines/sites
Result & Added Value
- ML models to predict failure probabilities before they occur based on production and measurement data
- Data-driven optimization allowing iterative improvement
- Est. 1m € EBITDA gains from implementation
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