Credit evaluation system table
| Evaluation dimension | Specific indicator | Weight | Data source | Scoring rule |
|---|---|---|---|---|
| Response efficiency | Average time for trapped person rescue | 30% | Regulatory platform alarm records | <30 min: 5 points; 30–60 min: 3 points; >60 min: 1 point |
| Maintenance quality | AI prediction fault hit rate | 25% | PHM engine output vs maintenance records | Hit rate >90%: 5 points; 80%–90%: 4 points… |
| Operational standards | Electronic maintenance order completion rate | 20% | Maintenance app upload records | Completion rate 100%: 5 points; 1 point deducted for every 10% decrease |
| Historical credit | Previous annual rating | 15% | Platform historical data | Grade A: 5 points, Grade B: 4 points, Grade C: 3 points, Grade D: 1 point |
| User evaluation | Owner satisfaction score | 10% | “Zheliban” mini program feedback | Average score ≥4.5: 5 points… |
| Evaluation dimension | Specific indicator | Weight | Data source | Scoring rule |
|---|---|---|---|---|
| Response efficiency | Average time for trapped person rescue | 30% | Regulatory platform alarm records | <30 min: 5 points; 30–60 min: 3 points; >60 min: 1 point |
| Maintenance quality | AI prediction fault hit rate | 25% | PHM engine output vs maintenance records | Hit rate >90%: 5 points; 80%–90%: 4 points… |
| Operational standards | Electronic maintenance order completion rate | 20% | Maintenance app upload records | Completion rate 100%: 5 points; 1 point deducted for every 10% decrease |
| Historical credit | Previous annual rating | 15% | Platform historical data | Grade A: 5 points, Grade B: 4 points, Grade C: 3 points, Grade D: 1 point |
| User evaluation | Owner satisfaction score | 10% | “Zheliban” mini program feedback | Average score ≥4.5: 5 points… |