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ScopePeriod

Drum Thresher TH-02

Asset 360 · Thresher · Mill A
TH-02RUNNINGCriticality AThresher
Manufacturer
Nusantara Engineering
Model
DT-1800
Location
Mill A · Threshing
Commissioned
2009-10-25
Age
17 years
Operating hours
94,263 h
Utilization
93%
Availability (90 d)
96.2%
MTBF / MTTR
2,096 h / 9 h
Replacement cost
Rp 1.94 bn
Sensors
vibration, current, rpm, temperature
Region
Sumatra
78/100
Health score

Predictive maintenance

Asset Failure Prediction v3.2 · gradient-boosted survival model on IoT, SCADA and CMMS history · refreshed 06:52

Confidence79%
Health score
78/100
Failure probability
22%7 days
Remaining useful life
45days
Anomaly score
0.410–1
Likely cause
Minor imbalance — within tolerance
Recommendation
Continue monitoring
What the model sees
Confidence79%
All monitored signals are within normal bands. Failure probability 22% over 7 days; continue condition monitoring and scheduled PM.
Why this prediction — top drivers (pp of failure probability)
Baseline failure rate for class ≈ 12% · bars push probability up or down
Vibration RMS trend
+7.6 pp
Motor current / load
+4.7 pp
Age / operating hours
+4.3 pp
Speed deviation
+3.1 pp
Temperature deviation
+1.8 pp
Recent preventive maintenance
−2.0 pp
◀ lowers predictionraises ▶

Sensor trends & failure forecast

60-day history (daily) · dashed = model forecast · anomaly began 14 Sep

Vibration · mm/s RMS
Warning 4.5 · Alarm 7.1 mm/s RMS

Maintenance Decision Intelligence

Weighs failure probability, criticality, downtime impact, repair vs replacement cost, spare availability and production schedule

Decision inputs
Failure probability (7 d)22%
CriticalityClass A · production-critical
Downtime impactRp 165 m / h
Planned repair costRp 58 m
Replacement costRp 1.94 bn
Spare availabilityBR-22220: in local store
Production schedulePeak crop · next shutdown Sun
Option suitability
Monitor68
Risk too high to run without intervention
Schedule maintenance63
Fits next planned shutdown; balances risk and production
Replace asset37
Asset 17 yrs — evaluate capex replacement
Replace component21
No single failing component identified
Repair now2
Stops the line during peak crop — restan and emergency premium
Scenario comparison
OPTION A
Repair immediately
Stop line now, replace component using emergency transfer
Failure risk2%
Expected costRp 474 m
Planned downtime4 h

Lowest risk, but interrupts peak-intake processing and creates restan.

OPTION B
Repair in low-production window
Replace at next planned shutdown
Failure risk8%
Expected costRp 137 m
Planned downtime4 h

Balances failure risk against production loss at the next planned shutdown.

Recommended
OPTION C
Continue monitoring
Run to next scheduled shutdown (14 days)
Failure risk22%
Expected costRp 340 m
Planned downtime0 h

Recommended — risk is low; keep condition monitoring and standard PM.

Recommendation: Monitor
Confidence80%
Continue monitoring. Option C expected cost Rp 340 m vs Rp 340 m if left to run; residual risk 22%.
Estimated impact based on synthetic scenario assumptions. Recommendation requires validation by the Maintenance Manager.

Spare parts availability

Key parts for TH-02 across the warehouse network · home store WH-01

Cross-module: Inventory AI
BR-22220 · Spherical roller bearing 22220 (thresher)
Lead time 35 d · Rp 9.7 m/pcs · 30-d demand 0.8
2 in home store
WH-01 · Mill A (home)
2 pcs · SS 1
WH-02 · Mill B
6 pcs · SS 1
CHN-TH-40 · CHN-TH-40
Lead time 14 d · Rp 0/pcs
0 in home store
Not stocked — procured on demand.
Open Spare Parts Intelligence

Maintenance records

CMMS history, open work orders, failure events and spares

No open work orders — asset on standard PM schedule.
Synthetic asset data and simulated model output. Maintenance recommendations are decision support requiring validation by qualified personnel.
V-TEKI — IT & Business ConsultingDeveloped by V-TEKI · IT & Business ConsultingPrime Agri AI Intelligence Platform — prototype. All operational records are synthetic; model outputs are simulated; financial impacts are scenario estimates; recommendations require human validation. No actual company confidential data is used.