With the lockdown causing severe restrictions for mining operations in South Africa, mining companies have had to revisit strategic planning and adjust objectives for the current financial year, states former University of Pretoria (UP) Graduate Schoo of Technology Management Professor Krige Visser.

Performance in relation to these objectives must be monitored to allow for corrective action if actual performance deviates significantly from planned performance and, therefore, affects the ability of a business to meet its goals.

He adds that, similarly, maintenance performance measurement is required to ensure that maintenance objectives are achieved and add value to the company.

Maintenance management is an essential activity in asset-intensive organisations such as mining companies. “The primary goal of maintenance management is to achieve the right balance between cost, risk and the performance of physical assets,” Visser states.

He adds that maintenance management also includes the availability of physical assets, which depend on reliability and maintainability.

Reliability can be improved through preventive maintenance, which ensures that assets are in a good working condition. There are two types of preventive maintenance – usage-based maintenance and condition-based maintenance.

Usage-based maintenance takes the average daily usage of an asset into account and uses it to forecast dates for maintenance, while condition-based maintenance monitors the actual condition of an asset. The latter dictates that maintenance should be performed only when certain indicators show signs of decreasing performance or upcoming failure.

Another factor of maintenance management is asset replacement. “As an asset ages, the maintenance costs increase and reach a point where it becomes uneconomical to extend the life of the asset, leaving assets owners with the decision of when to replace the asset,” Visser says.

He cites a study on an electric rope shovel at a surface coal mine that was used to develop a methodology that determined the optimum replacement age of heavy mobile equipment that was close to the end of its life.

As accurate failure-data for the components of the rope shovel was not available to perform detailed financial calculations, a simulation model was developed. The model used failure and impact assessments that were provided by experts.

“The solution provided by the stochastic model calculated the expected loss of rope shovel as a function of machine-age with a 90% confidence interval. The information was subsequently used to determine an optimum replacement age,” he explains.

The study demonstrates that the optimum replacement age of any heavy mobile equipment can be obtained by modelling the expected losses, owing to the failure of critical end-of-life components, when accounting for the uncertainty in dates obtained from the experts, Visser adds.

“Mining companies need such decision tools and methods to determine optimum operational parameters and replacement ages for mobile and static equipment.”