Comparison of Alternative Truck Maintenance Strategies using Simulation

Recently the Australian mining industry has focussed on improving the efficiency of existing operations and lowering production costs.
This study explored alternative surface mining truck maintenance strategies, namely condition based maintenance (CBM) and clustered maintenance (CM). The strategies were compared using performance metrics such as truck availability, workshop utilisation and efficiency.
The study examined the application of CBM and combined CB and CM maintenance (CBCM) through computer modelling and simulation. Multiple models, each representing a single maintenance strategy, were constructed. Initial results were analysed before the completion of a sensitivity analysis, which established the influence of key variables on maintenance strategy performance.
The study shows that both CBM and CBCM reduced workshop utilisation, increasing truck availability by 3% and 5%, respectively, over the base case. CBCM provides the greatest reduction in individual maintenance bookings, substantially reducing workshop related delays and increasing workshop efficiency.
Further analysis of CBCM showed that the critical condition threshold governs maintenance strategy performance, while the diagnostic condition threshold largely affects clustering efficiency.
The study concludes that operators who implement CBM should realise significant benefits in terms of both increased production, due to higher truck availability, and lower operating costs.