Digital Twin & Production Line Simulation
Customer
Glass Bottle Manufacturer
Developing tools on Foundry and applying causal models to identify optimal steps in glass bottle production process to increase yield of production line
Challenge
- Want to improve yield on production line form 86% to 90%
- Already identified step in process where gain could be realised
- But no way to automatically prioritise sensor data which should be further analysed
- Goal is to apply ML models to identify most promising captors to improve yield
Solution
- Initially built E2E model of yield on production line, but hit data quality roadblock
- Shifted towards:
- developing tool on Foundry to surface “golden production parameters” when production quality was high
- using causal models to understand optimal actions to stabilise first step of production process
Business impact
- Highlighted data quality issues and suggested next best steps for improvements
- Demonstrate Foundry’s ability to replace existing system
- Trained key internal stakeholders on Foundry platform
