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Dr. Eugene Ben-Awuah

IAMGOLD Research Fellow


Dr. Eugene Ben-Awuah is an Associate Professor of Mining Engineering at the Bharti School of Engineering and Computation and a IAMGOLD Research Fellow in Open Pit Mining. As an IAMGOLD Research Fellow, Dr. Ben-Awuah is working on the following projects:

1)    Strategic Mining Options Optimization: A Theoretical Framework for Resource Development Planning

Description: The problem of optimizing reserve exploitation depends largely on the mining option used in the extraction. This research proposes to develop and implement methodologies and tools for strategic mining options optimization in relation to open pit and/or underground mine planning in the presence of uncertainty for IAMGOLD’s Westwood and Cote Gold projects. This project is made up of research work in four parts: 1) A framework for open pit and underground mining options optimization; 2) An optimization framework for strategic underground mine planning; 3) A stochastic mathematical programming framework to evaluate the impact of different strategic mining options (open pit and/or underground mining) in extracting a mineral resource; and 4) Assess the practical feasibility of generated results and solution optimality of large-scale problems. Comprehensive numerical models will be developed, implemented and verified with data from IAMGOLD.

Status: Bright Oppong Afum, a PhD student, completed work on Parts 1 and 4 of this project in April 2021. Emmanuel Appianing, a PhD student, started working on Parts 2 and 4 of this project since May 2018, and is ongoing.

2)    Intelligent Mine Planning Decision-making System for Mining Operations

Description: With the introduction of autonomous haulage systems, trucks have the capacity to operate continuously uninterrupted following dispatch assignments. This research will seek to continuously optimize the short-term mine plan and haulage fleet size as minor operational changes occur leading to suboptimal fleet assignments. The research will focus on developing: 1) an optimization framework that determines the number and sizes of shovel and trucks, and allocates shovel to trucks in an intermittently changing operational environment; 2) an artificial intelligence (AI) framework that seeks to monitor the fleet management and short-term mine planning data patterns, and use this knowledge to provide forecast indicators on fleet sizing and allocation; and 3) a smart mining agent based on artificial intelligence (AI), data mining and simulation to manage the mining strategy for short-term mine planning in real time through blending and reconciliatory optimization.

Status: A PhD student, Pedro Pablo Vasquez Coronado has been recruited to work on the simulation model for this project since September 2019. Solomon Acheampong, a MASc student, is working on the smart mining agent in Parts 1, 2 and 3 of this project since September 2020, and is ongoing.


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