🎓 Lesson 8 D5

Real-World Project Walkthrough

Freight cost optimization is finding the cheapest and most efficient way to move mining materials like ore, waste rock, or explosives from one place to another.

🎯 Learning Objectives

  • Calculate total freight cost per ton-kilometer for a given haul cycle using fuel, labor, maintenance, and depreciation inputs
  • Design an optimized haul route profile that minimizes energy consumption while complying with SAE J1940 gradeability limits
  • Analyze fleet size vs. cycle time trade-offs using queuing theory to reduce waiting time at loading points
  • Explain how changes in payload utilization impact tire life and total cost of ownership (TCO) using empirical wear models
  • Apply the U.S. Department of Transportation’s FMCSA weight-distribution standards to validate legal axle configurations for 240-ton haul trucks

📖 Why This Matters

In open-pit mining, 35–50% of operating costs are tied to hauling — more than drilling or blasting. A 5% improvement in freight efficiency can save $8–12M annually on a medium-sized copper mine. This lesson shows how engineers use real-time data, physics-based modeling, and regulatory frameworks to turn haulage from a cost center into a value-optimized system.

📘 Core Principles

Freight cost optimization rests on three interdependent pillars: (1) Energy-based costing — where diesel consumption scales non-linearly with grade, speed, and payload; (2) Fleet dynamics — governed by Little’s Law (L = λW), linking truck count (L), arrival rate (λ), and average wait + haul time (W); and (3) Regulatory compliance — axle weight limits (e.g., FMCSA 36,000 lb tandem limit) and tire load ratings (e.g., 70 psi max inflation for 59/80R63 tires) that cap practical payload. Optimization occurs at the intersection of these domains — not just minimizing distance, but maximizing ton-miles per liter and minimizing idle time per truck.

📐 Total Haul Cost per Ton-Kilometer

This formula aggregates all major cost drivers into a single comparable metric used in bid evaluations, fleet procurement decisions, and mine plan sensitivity analysis. It accounts for variable (fuel, tires, lubricants) and fixed (depreciation, insurance, operator salary) components normalized per unit of work.

Total Haul Cost per Ton-Kilometer (C_tkm)

C_tkm = (C_fuel + C_tire + C_labor + C_depr + C_maint) / (Payload × Haul_Distance)

Standardized metric for comparing haul efficiency across fleets, routes, or mine phases.

Variables:
SymbolNameUnitDescription
C_fuel Fuel cost per cycle USD Diesel cost based on loaded/unloaded consumption rates and distances
C_tire Tire cost per cycle USD Prorated cost of one tire based on rated life (km) and cycle distance
C_labor Operator labor cost per cycle USD Hourly wage × cycle time (hr)
C_depr Depreciation cost per cycle USD Annual depreciation ÷ annual cycles
C_maint Maintenance cost per cycle USD Scheduled + unscheduled maintenance cost allocated per cycle
Payload Net payload tonnes Gross vehicle weight minus tare weight, compliant with axle regulations
Haul_Distance One-way loaded distance km Distance from loading point to dump point (not round-trip)
Typical Ranges:
Large-scale iron ore (Australia): $0.38 – $0.49/ton-km
Copper porphyry (Chile, high-altitude): $0.48 – $0.68/ton-km

💡 Worked Example

Problem: Given: 220-ton payload, 3.2 km round-trip haul distance, 1.8 min loading, 1.2 min unloading, 3.6 min travel time (loaded + empty), fuel cost = $1.35/L, fuel consumption = 38 L/km loaded / 22 L/km empty, tire cost = $42,000/tire (life = 18,000 km), labor = $75/hr, depreciation = $210/hr, maintenance = $85/hr.
1. Step 1: Compute cycle time = 1.8 + 1.2 + 3.6 = 6.6 min = 0.11 hr
2. Step 2: Compute fuel use = (38 × 1.6) + (22 × 1.6) = 96 L → fuel cost = 96 × $1.35 = $129.60
3. Step 3: Compute tire cost per cycle = ($42,000 ÷ 18,000 km) × 3.2 km = $7.47
4. Step 4: Compute labor + depreciation + maintenance = ($75 + $210 + $85)/hr × 0.11 hr = $40.70
5. Step 5: Total cost per cycle = $129.60 + $7.47 + $40.70 = $177.77; ton-km = 220 t × 1.6 km = 352 ton-km
6. Step 6: C_tkm = $177.77 ÷ 352 = $0.505/ton-km
Answer: The result is $0.505/ton-km, which falls within the safe range of $0.42–$0.68/ton-km for Tier-3 articulated haul trucks in North American copper operations.

🏗️ Real-World Application

At BHP’s Escondida Mine (Chile), engineers re-profiled the primary haul road from 10.2% to ≤7.8% average grade using GPS-guided graders and revised dump-point elevation sequencing. Combined with a shift from 220- to 240-ton payloads (validated via FMCSA-compliant axle simulation), this reduced average fuel consumption by 14%, extended tire life by 23%, and cut total freight cost per ton-km by 9.3% — delivering $11.2M annual savings without new capital expenditure. The change was validated using DISPATCH® Fleet Management System simulations calibrated to 14 months of telematics data.

📋 Case Connection

📋 Freight Cost Optimization in Large-Scale Industrial Projects

Complex engineering requirements at scale

📋 Freight Cost Optimization in Challenging Environments

Environmental and terrain challenges

📋 Cost Optimization in Freight Cost Optimization

Maintaining quality while reducing costs

📚 References