Angel Angelov


Technical Manager

Angel Angelov is a distinguished mining engineer with a decade of experience in mine design and planning, specializing in both underground and open-pit mining across various commodities. His career highlights include impactful roles at BHP and Glencore, where he demonstrated expertise in enhancing mining operations through innovative optimization and mine planning techniques. Angel's adept use of advanced computational tools, particularly Pseudoflow algorithms for mine design and scheduling, distinguishes his work. His approach, integrating Activity-Based Costing early in mine planning, has led to more economically and environmentally sustainable mining practices. Angel earned a B.Eng. Honours degree in Mining Engineering from the University of Pretoria in South Africa, underpinning his practical experience with solid academic foundations. As a speaker, Angel's ability to present complex concepts accessibly, combined with his commitment to sharing knowledge, makes him a respected figure in mining conferences worldwide. His insights into leveraging Pseudoflow for mine optimization have earned him recognition and appreciation from peers.

DigiTech’24 Conference (Session 3)
18 April 2024 / 14:00 - 15:30 | Sary Arka 3

Leveraging Pseudoflow for Enhanced Underground Mine Design and Scheduling: A Case Study

In the intricate domain of underground mine design and scheduling, the quest for optimization and efficiency is perpetual. Traditional methodologies, heavily reliant on spreadsheet software like Excel and final valuation models for analysis, have served the mining industry for decades. However, the complexity of modern mining operations, combined with increasing economic and environmental constraints, necessitates a more sophisticated and holistic approach. This presentation introduces a groundbreaking case study on the application of Pseudoflow algorithms in underground mine design and scheduling, marking a significant departure from conventional methods. Pseudoflow, a potent computational technique, is renowned for its ability to solve complex network flow problems efficiently. By applying Pseudoflow to the challenges of underground mine design and scheduling, our team has successfully developed a methodology that not only enhances the accuracy of extraction planning but also significantly improves the cost-effectiveness of mining operations. Central to our approach is the integration of Activity-Based Costing (ABC) at the very onset of mine design and scheduling stages. This integration provides a granular view of cost allocation and enables a more strategic and economically viable extraction plan. Our case study details the systematic application of Pseudoflow in a real-world mining scenario, outlining the methodological shifts from traditional spreadsheet-based analyses to a more dynamic and comprehensive optimization framework. By incorporating Pseudoflow, we demonstrate a marked improvement in operational efficiency, cost reduction, and the strategic alignment of mine design with financial objectives.