Decision Engine Output
Which Machine Should We Maintain First?
“Highest failure probability ≠ highest business priority.”
Machine M-202
Servo Press
Decision Priority
71
- Failure Probability
- 82%HIGHER
- Operational Criticality
- Medium
- Production Dependency
- Low
- Backup Capacity
- Available
- Estimated Failure Downtime
- 4 hours
- Estimated Business Exposure
- Rp 42M
VERSUS
Machine M-103
CNC Machining Center
Decision Priority
87
- Failure Probability
- 78%
- Operational Criticality
- HIGH
- Critical Customer Orders
- 3
- Backup Capacity
- Limited but manageable
- Estimated Failure Downtime
- 12 hours
- Estimated Business Exposure
- Rp 145M
Rank changes when context is added
AI PrioritizationBy failure probability
By decision priority
#1M-20282%
#2M-10378%
#1M-10387
#2M-20271
AI Prioritization
Generative AI Explanation#1M-103Decision Priority 87
#2M-202Decision Priority 71
M-202 has a higher predicted failure probability.
However, M-103 receives higher operational priority because its potential failure has significantly greater production, customer, downtime and financial consequences.
M-202 is not ignored: it is queued for Sunday 08:00 with backup press-cell coverage.
Factor-by-factor comparison
Decision Engine Output| Factor (weight) | M-202 | M-103 | |
|---|---|---|---|
| Failure Risk (25%) | 89 | 84 | |
| Operational Criticality (20%) | 65 | 95 | |
| Production Impact (20%) | 55 | 90 | |
| Customer / SLA Impact (10%) | 35 | 85 | |
| Resource Availability (10%) | 100 | 80 | |
| Spare Part Availability (5%) | 100 | 100 | |
| Safety Risk (5%) | 90 | 60 | |
| Cost Exposure (5%) | 28 | 97 | |
| Decision Priority Score | 71 | 87 |
Predictive Maintenance
asks:
“Which machine is more likely to fail?”
Decision Intelligence
asks:
“Which problem should we solve first?”