# Case Studies

## Domestic (China)

### Huawei AI+Manufacturing
- **Scenario**: Visual inspection on PCB assembly line
- **Solution**: Self-developed CNN + edge deployment on Atlas AI accelerator
- **Result**: Defect miss rate reduced from 3% to 0.3%; 24/7 unattended inspection

### Shandong AI+Manufacturing
- **Scenario**: Process optimization for petrochemical production
- **Solution**: Digital twin + Bayesian optimization for distillation column
- **Result**: Energy consumption reduced 8%; yield improved 3.2%

### Desay SV Automotive Electronics
- **Scenario**: Predictive maintenance for SMT placement machines
- **Solution**: Vibration sensor + LSTM model; 14-day prediction window
- **Result**: Unplanned downtime reduced 45%; maintenance cost reduced 30%

### Baidu Industrial Cloud (Kaiwu)
- **Scenario**: Quality prediction for steel continuous casting
- **Solution**: Multimodal (sensor + image) + PaddlePaddle edge deployment
- **Result**: Quality prediction accuracy 92%; defect rate reduced 25%

### Hunan Steel (Xianggang)
- **Scenario**: Surface defect detection on hot-rolled steel
- **Solution**: Few-shot learning for rare defect categories + active learning
- **Result**: New defect category onboarding from 2 weeks to 2 days

### Staro (Xingrui) Predictive Maintenance
- **Scenario**: CNC machine tool predictive maintenance
- **Solution**: Spindle current + vibration fusion; physics-informed features
- **Result**: 72-hour advance warning; false alarm rate < 8%

## International

### Siemens Industrial Copilot & Digital Twin 2.0
- **Solution**: LLM-based industrial copilot + physics-accurate digital twin
- **Result**: Engineering time reduced 30%; real-time what-if simulation

### GE Supply Chain AI
- **Scenario**: Supply chain disruption prediction for aviation parts
- **Solution**: Graph neural network on supplier network + NLP on news/events
- **Result**: Disruption prediction 2 weeks ahead; inventory optimization 15%

### Palantir Foundry + Ontology
- **Scenario**: Multi-source industrial data integration
- **Solution**: Ontology-based semantic layer unifying OT/IT/ET data
- **Result**: Data integration time from months to weeks; cross-system queries

### Tesla Gigafactory
- **Scenario**: Real-time quality control across 10K+ sensors
- **Solution**: Edge ML pipeline + centralized retraining; data flywheel
- **Result**: Defect detection in < 100ms from sensor to alert

### Schaeffler Predictive Maintenance
- **Scenario**: Bearing failure prediction across global plants
- **Solution**: Physics-informed ML + federated learning across plants
- **Result**: 85% prediction accuracy; 30% maintenance cost reduction