Operations Research in Mining

1. Introduction

Operations Research (OR) plays a crucial role in optimizing mining operations across the entire value chain—from exploration and extraction to processing, transportation, and closure. By applying mathematical modelling, simulation, decision science, optimization, and data analytics, OR enables mining companies to improve efficiency, maximize output, reduce cost, enhance safety, and manage risk.

This course provides participants with the analytical tools, models, and quantitative techniques used to solve complex mining problems. It covers optimization of mine design, scheduling, haulage systems, equipment allocation, supply chain logistics, and overall operational performance. The programme is designed to empower professionals with advanced decision-making capabilities in modern, data-driven mining environments.

 

2. Training Objective

The course aims to:

• Introduce participants to the fundamental principles of operations research applied to mining.
• Equip learners with quantitative tools for modelling and solving mining operational challenges.
• Enable participants to conduct optimization for mine design, scheduling, and resource allocation.
• Develop skills in simulation, decision analysis, linear and nonlinear programming.
• Strengthen analytical capabilities for evaluating mining systems using real-life datasets.
• Familiarize participants with OR software tools, digital technologies, and algorithmic techniques.
• Support strategic decision-making through scenario analysis and predictive modelling.

 

3. Targeted Group

This course is designed for:

• Mining engineers and mine planners
• Operations managers and production supervisors
• Mineral processing and plant engineers
• Industrial engineers and logistics officers
• Mine analysts, data scientists, and optimization specialists
• Government regulators, inspectors, and policy officers
• Consultants and project developers
• Postgraduate students and graduate engineers seeking quantitative mining skills

 

4. Course Duration

Total Duration: 16 Modules

Delivery options include:

• 16-day intensive professional workshop, or
• 8-week modular programme, or
• 4-month blended certificate course with assignments and applied projects

Each module includes practical tasks, case studies, and problem-solving sessions.

 

5. Training Methodoloy

FOTADE employs a dynamic, practice-oriented approach, including:

• Expert-led lectures and demonstrations
• Mathematical modelling exercises
• Hands-on use of OR software (e.g., MATLAB, Python, LINGO, Arena Simulation)
• Case studies from real mining operations
• Group problem-solving and optimization challenges
• Data analysis, simulations, and scenario testing
• Quizzes, assignments, and workshops
• Capstone optimisation project and evaluation

 

6. Course Content

Module 1: Introduction to Operations Research in Mining

• Scope, role, and importance of OR
• Decision science foundations

Module 2: Linear Programming and Optimization Techniques

• Formulating mining optimization problems
• Simplex method and duality concepts

Module 3: Nonlinear and Integer Programming

• Mixed-integer programming (MIP)
• Applications in mine scheduling

Module 4: Queuing Theory and Simulation in Mining

• Queuing models for equipment and trucks
• Discrete-event simulation

Module 5: Mine Scheduling and Production Planning

• Long-, medium-, and short-term scheduling
• Optimization of production cycles

Module 6: Truck–Shovel Optimization and Haulage Systems

• Fleet management
• Dispatch optimization techniques

Module 7: Mine Layout and Design Optimization

• Pit design, stope design
• Geotechnical constraints in OR modelling

Module 8: Equipment Allocation and Maintenance Optimization

• Maintenance scheduling
• Reliability-centred optimization

Module 9: Mineral Processing Plant Optimization

• Throughput modelling
• Bottleneck analysis

Module 10: Supply Chain and Logistics Optimization in Mining

• Inventory, stockpile, and blending optimization
• Transportation and distribution networks

Module 11: Probabilistic Modelling and Risk Analysis

• Stochastic processes
• Risk quantification and mitigation

Module 12: Decision Analysis and Multi-Criteria Evaluation

• Cost–benefit analysis
• Analytic Hierarchy Process (AHP)

Module 13: Data Analytics and Machine Learning in OR for Mining

• Predictive modelling for operational efficiency
• Integration of OR with AI tools

Module 14: Software Tools for Mining Optimisation

• Practical sessions with optimization and simulation software
• Model building and validation

Module 15: Sustainable Mining and OR Applications

• Energy optimization
• Environmental constraints in OR models

Module 16: Capstone Project – Comprehensive Mining Optimization Study

• Participants develop a full OR model for a mining operation
• Includes scheduling, haulage, processing, and cost optimization
• Presentation and professional review

 

7. Expected Outcomes

Upon successful completion, participants will be able to:

• Formulate and solve complex mining operational problems using OR techniques.
• Develop quantitative models for optimizing production, haulage, scheduling, and plant performance.
• Use optimization, simulation, and data analytics tools effectively.
• Evaluate system performance and perform scenario-based decision analysis.
• Improve productivity, reduce operational cost, and enhance safety using OR-driven insights.
• Integrate digital technologies, AI, and predictive tools into mining operations.
• Prepare technical reports and optimization proposals for decision-makers.
• Demonstrate advanced problem-solving, analytical, and strategic planning capabilities.

 

8. Certificate of Completion

Participants who complete all modules, practical tasks, and the capstone project will receive:

Certificate of Completion in Operations Research in Mining

Issued by:

FOTADE Training, Research and Resource Development Centre

This certificate recognizes the participant’s advanced competence in applying OR tools and techniques to mining operations.