Dion de Villiers studies how simulation can expose bottlenecks and productivity opportunities across an entire mechanised underground mining process rather than optimising one machine in isolation.
Research approach
The study developed a simulation methodology and applied it across three mine case studies. Operating data and process logic are translated into models that reproduce interactions between equipment, activities, delays and production constraints.
This allows proposed changes to be tested in a controlled environment before implementation. The model can show where an apparent local improvement simply moves a bottleneck downstream, and where a change produces a genuine system-level productivity gain.
Programme journey
Dion completed his honours degree with distinction in 2021 and began MEng research in 2022. His study became part of the RAMMS productivity-modelling portfolio and contributes a practical, case-based complement to Hloni Manyakoana’s production-cycle optimisation work.
The research was supervised by Johann Wannenburg. By the second quarter of 2026, the three-case study and dissertation were complete and awaiting final supervisor approval before formal submission.