🎓 Lesson 2
D2
Mine Planning & Scheduling Fundamentals
Mine planning and scheduling is the process of deciding where, when, and how much to mine—and in what order—to safely and profitably extract resources over time.
🎯 Learning Objectives
- ✓ Calculate optimal bench height and advance rate for a given equipment fleet and orebody geometry
- ✓ Design a 3-year production schedule using precedence constraints and resource capacity limits
- ✓ Analyze schedule robustness by quantifying critical path sensitivity to delay in key activities
- ✓ Explain the trade-offs between short-term grade control and long-term NPV optimization
- ✓ Apply Lerchs-Grossmann (LG) algorithm logic to validate pit shell feasibility
📖 Why This Matters
Every dollar spent on mining equipment, labor, or energy is only justified if the material it moves contributes to profitable, safe, and sustainable production. Poor planning leads to bottlenecks, stranded ore, excessive waste handling, and missed market opportunities—costing mines millions annually. In 2023, McKinsey reported that top-quartile mines achieve 15–20% higher NPV through disciplined, data-driven scheduling—proving that planning isn’t paperwork; it’s the engine of value creation.
📘 Core Principles
Mine planning rests on three interdependent pillars: (1) Geospatial fidelity—the accurate representation of orebody geometry, grade distribution, and rock mass properties in 3D block models; (2) Temporal logic—sequencing extraction to respect geotechnical stability (e.g., slope angles, pit wall sequencing), equipment mobility, and infrastructure development timelines; and (3) Economic optimization—balancing cut-off grade selection, blending requirements, capital timing, and discounting effects. Tactical scheduling further introduces resource constraints (e.g., shovel availability, truck cycle times) and stochastic elements (e.g., weather, equipment reliability). Modern practice increasingly integrates uncertainty via conditional simulation and scenario-based scheduling.
📐 Production Rate Calculation (Tactical Level)
This formula estimates achievable daily production volume based on fleet capacity and operational efficiency—critical for validating schedule feasibility against equipment limits.
Daily Production Capacity
P = N_s × C_c × V_b × H_e × A_f × ρEstimates daily tonnage production capacity based on shovel fleet parameters and material density.
Variables:
| Symbol | Name | Unit | Description |
|---|---|---|---|
| P | Daily production | t/day | Total tonnes extracted per day |
| N_s | Number of shovels | unit | Active shovels in operation |
| C_c | Cycles per hour | cycles/hr | Average shovel cycle rate |
| V_b | Bucket volume | m³ | Heaped bucket capacity |
| H_e | Effective hours per day | hr/day | Scheduled operating time minus planned maintenance |
| A_f | Fleet availability factor | decimal | Fraction of time equipment is operational (0.85–0.95 typical) |
| ρ | Bank density | t/m³ | In-situ density of blasted material |
Typical Ranges:
Large open-pit copper mine: 25,000 – 45,000 t/day
Medium gold operation: 8,000 – 15,000 t/day
💡 Worked Example
Problem: A mine operates 3 hydraulic shovels (each 55 m³ bucket capacity), each completing 4.2 cycles/hour, with 18.5 effective hours/day and 92% fleet availability. Each truck carries 170 t/load; average bank density = 2.4 t/m³. Calculate daily production in tonnes.
1.
Step 1: Shovel output per hour = 3 shovels × 4.2 cycles/hr × 55 m³/cycle = 693 m³/hr
2.
Step 2: Daily shovel output = 693 m³/hr × 18.5 hr/day × 0.92 = 11,760 m³/day
3.
Step 3: Convert to tonnes = 11,760 m³/day × 2.4 t/m³ = 28,224 t/day
Answer:
The result is 28,224 t/day, which falls within the safe range of 25,000–32,000 t/day for this fleet configuration.
🏗️ Real-World Application
At Newmont’s Boddington Mine (Western Australia), integrated short-term scheduling reduced ore loss by 8% and dilution by 12% after implementing a grade-controlled, GPS-guided blast design coupled with real-time haul truck dispatch linked to a dynamic 7-day schedule. The system used block model updates from daily survey and assay data, recalculating optimal dig locations every 4 hours—demonstrating how tight feedback loops between planning, execution, and measurement drive continuous improvement.
🔧 Interactive Calculator
🔧 Open Mine Planning & Scheduling Calculator📋 Case Connection
📋 Mine Planning & Scheduling Case Study 1
Inconsistent production scheduling due to inaccurate grade estimation and inflexible short-term plans, leading to 18% mo...
📋 Mine Planning & Scheduling Case Study 2
Inconsistent haul truck utilization due to static, annual mine plans that failed to account for real-time geotechnical v...