Christophar Chagwedera is a mechanical engineering and maintenance professional with more than two decades of experience in maintenance planning, execution, reliability and engineering supervision across mining and industrial settings. He is pursuing an MEng in Mechanical Engineering at the University of Pretoria. His research develops a Reliability, Availability, Maintainability and Cost (RAM-C)-based decision model for maintenance sourcing in mechanised mining.
Why maintenance sourcing needs a systems view
Mining equipment maintenance may be organised in-house, outsourced or through a hybrid arrangement. The choice can affect equipment performance and whole-of-life costs, yet it is often assessed mainly as a commercial decision. Christophar’s work seeks to make those broader consequences visible by considering reliability, availability, maintainability and cost alongside technical and operational factors.
The aim is not to prescribe one arrangement for every operation. Skills, spares, logistics, production demands and component failure behaviour vary between equipment and operating contexts. The proposed framework is intended to provide a structured way to compare alternatives using evidence and priorities relevant to the decision at hand.
Model structure and methods
The research uses a component-level approach, allowing assumptions and maintenance strategies to be examined for individual equipment components rather than relying only on a single equipment-level reliability measure. Weibull-based reliability modelling represents component failure-time behaviour, while an event-based simulation framework models the sequence of failures and maintenance interventions over an operating period.
The model includes corrective repair, component replacement, preventive maintenance and condition-based maintenance, together with maintenance durations, costs and availability calculations. Microsoft Excel supports model development and analysis, with Power Query used to prepare and organise data.
Progress and application
A component-level RAM-C structure has been developed for a mechanised load-haul-dump machine, alongside a classification approach for failure modes and mechanisms. The model has been evaluated using independent mining case studies to examine how it can represent component behaviour and the reliability, availability, maintainability and cost implications of maintenance interventions in different operating contexts.
The next phase builds on this work to develop an integrated maintenance-sourcing decision model. It will investigate how RAM-C outputs can be combined with technical, operational and economic criteria to compare insourcing, outsourcing and hybrid options. Further sensitivity analysis and refinement of model parameters will help assess the framework’s robustness and wider applicability.
The framework is intended to support, not replace, engineering judgement, site experience, original-equipment-manufacturer information or formal risk assessment. Its usefulness depends on the quality of available failure and maintenance data, and further validation against suitable evidence will be important as the work develops.
Christophar’s research is supervised by Professor Johann Wannenburg.