Design and Planning Fundamentals

🎯 Learning Objectives

✓ Calculate total freight cost per tonne-kilometer using real-time haul cycle data
✓ Design an optimized truck allocation plan for a given pit-to-plant material flow requirement
✓ Analyze the impact of payload underloading and overloading on fuel consumption and tire life
✓ Explain how haul road grade and curvature affect rolling resistance and overall freight cost
✓ Apply linear programming concepts to solve a simplified multi-origin/multi-destination haulage assignment problem

📖 Why This Matters

In open-pit mining, haulage typically accounts for 35–50% of total operating costs. A 5% reduction in freight cost per tonne can translate to millions in annual savings—without adding new equipment or expanding infrastructure. Poorly planned freight operations lead to excessive fuel use, premature tire failure, traffic congestion, and missed production targets. Mastering freight cost optimization directly impacts mine profitability, sustainability reporting (e.g., Scope 1 emissions), and regulatory compliance.

📘 Core Principles

Freight cost optimization rests on three interdependent pillars: (1) Cycle time physics—governed by distance, speed limits, grade, acceleration/deceleration, and queuing; (2) Fleet utilization economics—balancing fixed capital costs (truck depreciation, maintenance) against variable costs (fuel, tires, labor); and (3) System-level constraints—including dump/load point capacity, road width, traffic density, and GPS-based dispatch logic. Modern optimization also incorporates stochastic elements: payload variation due to shovel loading consistency, traffic interference, and weather-induced road conditions. Optimization shifts from 'maximizing truck throughput' to 'minimizing cost per delivered tonne', requiring trade-off analysis between speed, payload, and equipment longevity.

📐 Total Freight Cost per Tonne-Kilometer

This foundational metric aggregates all major haulage cost drivers into a single normalized unit, enabling cross-fleet and cross-site comparisons. It is essential for benchmarking and identifying improvement levers.

Freight Cost per Ton-km (Cₜₖ)

Cₜₖ = (C_fuel + C_labor_maint + C_tire) / (Payload × Haul_Distance)

Normalized cost metric enabling comparison across fleets, commodities, and sites.

Variables:

Symbol	Name	Unit	Description
C_fuel	Fuel cost per cycle	USD	Total fuel cost for one complete haul cycle (loaded + empty)
C_labor_maint	Labor and maintenance cost per cycle	USD	Hourly labor + scheduled maintenance allocated per cycle
C_tire	Tire cost per cycle	USD	Tire wear cost = distance × tire cost rate × payload
Payload	Average payload per cycle	tonnes	Measured net weight of material hauled per cycle
Haul_Distance	One-way loaded haul distance	km	Distance from loading point to dumping point

Typical Ranges:

Large iron ore mine (Pilbara): $0.65 – $0.95/t-km

Coal mine with short hauls (<2 km): $0.50 – $0.70/t-km

Hard rock copper with steep grades (>8%): $0.85 – $1.20/t-km

💡 Worked Example

Problem: A 220-ton rigid-frame haul truck completes 4.2 cycles/hour with average payload = 198 t, average haul distance = 3.8 km. Fuel cost = $1.25/L, fuel consumption = 38 L/km loaded + 22 L/km empty. Labor + maintenance = $85/hr/truck. Tire cost = $0.18/t-km. Calculate Cₜₖ.

1. Step 1: Compute loaded & empty distances per cycle: 3.8 km loaded, 3.8 km empty → total distance/cycle = 7.6 km

2. Step 2: Fuel cost/cycle = (38 L/km × 3.8 km) + (22 L/km × 3.8 km) = 228 L × $1.25/L = $285

3. Step 3: Labor/maintenance/cycle = $85/hr ÷ 4.2 cycles/hr = $20.24

4. Step 4: Tire cost/cycle = 7.6 km × $0.18/t-km × 198 t = $271.30

5. Step 5: Total cost/cycle = $285 + $20.24 + $271.30 = $576.54; Ton-km/cycle = 198 t × 3.8 km = 752.4 t-km

6. Step 6: Cₜₖ = $576.54 ÷ 752.4 t-km = $0.766/t-km

Answer: The freight cost is $0.766 per tonne-kilometer, which falls within the typical range of $0.65–$0.95/t-km for large-scale iron ore operations (CIM, 2022).

🏗️ Real-World Application

At Rio Tinto’s Pilbara operations (Australia), implementation of a GPS-enabled haul truck dispatch system combined with payload optimization reduced average freight cost by 12% over 18 months. By enforcing minimum 95% payload utilization (via shovel guidance algorithms) and re-routing trucks away from steep 12% grades where fuel penalty exceeded 23%, they cut fuel use by 8.7 L/t-km and extended tire life by 14%. The model used real-time telemetry from 220+ CAT 797F trucks and integrated with mine planning software to adjust fleet assignments daily based on updated ore/waste ratios.