245 2.2. Data Collection Standardized operational data (Aug 2023–Feb 2025) were compiled from digital FMS logs and structured manual records to enable consistent cross‑contractor comparison. The dataset includes production tonnage, equipment operating hours, fuel consumption, cycle time, and truck & digger productivity, capturing operational and maintenance-related variability. This consolidated dataset provides a robust basis for isolating FMS impacts relative to non-FMS operations. Fuel consumption was measured using L/h and L/ton, where L/h captures real-time usage and highlights idle inefficiencies (Choi et al., 2022a), while L/ton reflects energy intensity per output for benchmarking and emission reduction assessment (Bnouachir et al., 2023). Production Data were recorded in bank cubic meters (BCM) or metric tons to represent the cumulative material moved per contractor. BCM reflects in-situ volume, while tons better represent actual mass handled and improve fuel-per-tons calculations where material density varies. Cycle Time and Hauling Distance Haul-cycle duration and average distance per cycle were used to assess routing efficiency and equipment utilization. Reduced cycle times typically indicate higher productivity and improved fuel efficiency, supporting sustainability goals (Mnzool et al., 2024). Operating hours were monitored to normalize productivity and fuel metrics across downtime, maintenance, and shifts. Real-time FMS tracking reduces non-productive time and supports robust assessment of energy use, equipment efficiency, and emission intensity under controlled conditions. 2.3. Analysis Methodology Productivity Comparison is a quantitative assessment that was performed to compare FMS and non-FMS operations using standardized productivity metrics (Yeganejou et al., 2021). Digger productivity is defined as total material moved divided by actual operating hours, as shown in Equation (1), providing a consistent basis for evaluating equipment efficiency. 8%( : = < ; ℎ : (1) The formula above defines digger productivity (LMN O), expressed in tons per hour, by dividing the total production (P) by the total operating hours of the digger (Qℎ O). In contrast, the productivity of the truck was determined by considering not only the working hours but also the hauling distance. The total production was divided by operating hours and haul distance (in kilometers) (Choi et al., 2022b), as shown in equation (2): 8%( > = < ; ℎ > × :& (2) The formula defines truck productivity (LMN S, t/h·km) as total material transported (P) divided by truck operating hours (Qℎ S), multiplied by average haul distance (OT). This approach standardizes performance comparison by capturing both utilization and transport efficiency. Data from FMS-assisted and conventional operations were analyzed to identify productivity and efficiency gains enabled by digital fleet monitoring (Bnouachir et al., 2023). Fuel consumption per ton material: To evaluate fuel efficiency in mining operations, this study assesses fuel consumption per ton of material handled for both digger and truck using a ratio-based metric (Choi et al., 2022a). Fuel consumption is measured over a defined operational period and normalized by total material moved (ton). The primary indicator, the Digger Fuel Ratio, quantifies fuel usage per ton of production and is defined in Equation (3): : @A = @ ; ' (3)
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