Analysis of fuel consumption in a large surface mine, during more than 5000 cycles of material transportation, revealed considerable variability in the data. Truck fuel estimation based on the mining truck manufacturers' manuals/estimates is not capable of capturing this variability in the fuel consumption data. Partial least squares regression and autoregressive integrated moving average methods were employed to examine the effect of cyclic activities on fuel consumption, and to recommend relevant remedies for consumption reduction. Proper modifications of the operation can result in improved cycle times. Consequently, minimizing some cyclic activities would enhance energy efficiency. The truck "empty idle time" was a major contributor to unnecessary fuel consumption. Since the truck queues at shovels are a major component of the "empty idle time", decisions should be reviewed to reduce the truck queues at loading points. Improved dispatching strategies, optimal muck pile shape and size distribution, and improved shovel/loader operator skills are effective preventive measures to minimize truck flow bottlenecks at loading points, and thus to improve energy efficiency at mines. (C) 2016 Elsevier Ltd. All rights reserved.