Module 2
AI Predictive Locomotive Maintenance
Remaining useful life, component failure prediction and automatic maintenance scheduling for 14,880 locomotives across 42 sheds.
Fleet health score+0.6
88.4
Available locos94.2%
14,020
Under AI watch+8
112
Critical (RUL < 24h)Escalated
4
MTBF (avg)+3.2%
4,280 h
Cost saved YTDPredictive
₹412 Cr
Critical Locomotives
Ranked by AI failure probability
| Loco | Depot | Health | RUL | Status |
|---|---|---|---|---|
| WAP-7 · 37042 | Bhusaval | 62 | 48 h | AI Alert |
| WAP-5 · 35022 | Ghaziabad | 91 | 4,200 h | Nominal |
| WAG-9 · 31281 | Ajni | 78 | 1,080 h | Watch |
| WDG-4G · 70091 | Gooty | 84 | 2,400 h | Nominal |
| WAP-7 · 30291 | Erode | 12 | 6 h | Critical |
| WAG-12B · 60058 | Waltair | 88 | 3,100 h | Nominal |
Failure Trend (30d)
Predicted vs actual
Predicted 62Actual 51
Depot Performance
- Ghaziabad96%
- Erode74%
- Bhusaval82%
- Ajni88%
- Gooty91%