Fleet Analytics Dashboard

Mining Operations Intelligence

Fuel Efficiency — Lead-Normalized Analysis

Fuel consumption normalized by lead distance using linear regression — trucks only

Model-wise Fuel Efficiency Comparison

Average km/ltr, ltrs/trip, and ltrs/hr by equipment model

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Fuel vs KMs Travelled

Each dot = one vehicle, colored by model

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Fuel vs No. of Trips

Each dot = one vehicle, colored by model

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Lead-Normalized Fuel Anomaly Detection

Longer leads mean more cruising and fewer stop-start cycles per km, so ltrs/km typically decreases with lead. Per-model linear regression removes this lead effect — vehicles are flagged based on deviation from their expected fuel rate at their specific lead.

Model-wise Average Lead & Fuel Rate

Average one-way haul distance (km) and fuel consumption rate (ltrs/km) by model

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Lead vs Fuel Consumption Rate (Raw)

Each dot = one vehicle — shows lead's influence on ltrs/km before normalization

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Lead-Normalized Deviation

Each dot = one vehicle — deviation from expected fuel rate after removing lead effect. 0% = on regression line.

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Regression Model Fit

Linear regression parameters per equipment model

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Lead-Normalized Fuel Anomaly Report

Vehicles flagged based on ±20% deviation from regression-predicted fuel rate — 0 over-consumers, 0 efficient

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Model Summary

Aggregated fuel efficiency metrics per model (with lead)

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Vehicle-Level Detail

Individual vehicle fuel consumption, efficiency, and lead

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