Ryno Strydom examines predictive maintenance and digitalisation through a physical-asset-management lens. His research asks how new sensing, analytics and maintenance capabilities can be embedded in the way a mining organisation manages assets rather than deployed as isolated technology projects.
Connecting technology and asset decisions
Predictive maintenance is often discussed as an algorithmic problem, but implementation also depends on information quality, decision rights, work processes and the organisation’s ability to act on a warning. Ryno’s study positions digitalisation within that broader management system.
The work considers how modernisation changes the evidence available to maintenance teams and how that evidence can strengthen intervention planning, reliability and asset performance. It complements the programme’s equipment-level models by addressing the organisational layer needed to realise their value.
Progress
Ryno registered part-time in 2024 and completed the dissertation to the satisfaction of his internal supervisor. It was formally submitted for examination in 2026, with graduation expected later in the year. The research is supervised by Johann Wannenburg.