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ScopePeriod

Fleet & Logistics Intelligence

Harvest-to-mill dispatch optimization · Mill A supply baseAll operations
Why this matters
Confidence84%
Harvest-to-mill time at Mill A rose from 17 h to 26 h this week and explains 27% of the Mill A OER decline (22.3% → 21.6%). Older FFB builds free fatty acids and loses oil. The dispatch optimizer re-sequences truck pick-ups to evacuate the oldest ripe crop first and smooths arrivals at the mill.

Harvest-to-mill pipeline

Block → Collection point → Truck → Weighbridge → Mill · live flow simulation

Current practice
1. BLOCKS11of 30 in harvest round1,080 t FFB cut today2. COLLECTION POINTS186t waiting (restan)22 active CPs · first-come3. TRUCKS22trucks · 10 t117 trips · idle 52 min/truck4. WEIGHBRIDGE4.8min / ticket117 tickets · 2 bridges5. MILL A INTAKE55t/h capacityqueue 49 min avg · peak 9Peak queue 09–11 h (trucks)9Avg harvest-to-mill: 26 h · FFB > 24 h old: 58%Current practice: first-come dispatch, fixed truck-to-CP assignment

Objective & constraints

Adjust the scenario, then optimize

Objective: minimize
harvest-to-mill time · truck idle time · mill queue time · fuel cost
Avg harvest-to-mill
26.0h
current practice
Avg mill queue
49min
current practice
Truck idle
52min/truck
current practice
Fuel cost
24.8Rp m/day
current practice
Restan at CPs
186t
current practice
FFB > 24 h at intake
58%
current practice
OER effect · Mill A
Run the optimizer to estimate recovered OER.
H2M share of decline 27% × 0.7 pp, pro-rated by hours recovered vs the 9 h increase.
Solver notes
All constraints satisfied with slack; plan prioritises oldest ripe FFB at CP (restan) first.
Fleet utilization 79%Mill intake load 98%All constraints satisfied
Estimated impact based on synthetic scenario assumptions. Dispatch plans are decision support — the transport coordinator confirms before release.

Current dispatch schedule (baseline)

Run the optimizer to generate the AI plan

Mill A supply base · morning wave
AI priorityCPBlockFFB (t)ReadyTruckDispatchQueue (min)kmTime saved
0.97EB-CP-3B173806:30TR-00207:404818.4—
0.96EA-CP-1B034406:45TR-00608:105222.1—
0.58EE-CP-5B452107:00TR-01807:303516.8—
0.75EA-CP-4B073607:15TR-01109:056124.6—
0.67EB-CP-6B192907:40TR-01208:204019.7—
0.72EE-CP-2B433308:00TR-02309:405514.2—
0.79EB-CP-1B114008:20TR-01709:154420.3—
0.65EA-CP-7B092708:45TR-00110:105825.8—

Truck trip timeline

Current practice — run the optimizer to compare

Waiting at CPTravelMill queueWeigh & unload
06:0007:0008:0009:0010:0011:0012:0013:00
TR-002EB-CP-3 · 38 t
TR-006EA-CP-1 · 44 t
TR-018EE-CP-5 · 21 t
TR-011EA-CP-4 · 36 t
TR-012EB-CP-6 · 29 t
TR-023EE-CP-2 · 33 t
TR-017EB-CP-1 · 40 t
TR-001EA-CP-7 · 27 t
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.