Lesson 1Environmental and community data: dust monitoring (PM10/PM2.5), noise levels, truck traffic counts, complaint logs, water management, and tailings/erosion observationsThis lesson tackles environmental and community data needs like dust and noise monitoring, truck traffic logs, community complaints, water handling, and tailings checks, to ensure compliance, assess impacts, and foster good relations with locals and Brazilian regulators.
Dust (PM10/PM2.5) and meteorological dataNoise mapping and blasting impact recordsTruck traffic counts and road safety dataCommunity complaint logs and responsesWater balance, quality, and tailings checksLesson 2Drilling and blasting metrics: fragmentation, blasthole accuracy, powder factor, and pit wall stability indicatorsThis lesson examines drilling and blasting data for better fragmentation control, accurate blastholes, optimal powder use, and stable pit walls, connecting field data to loading, hauling, and crushing efficiency.
Drill pattern design and compliance dataBlasthole depth, deviation, and collar accuracyFragmentation size distribution measurementPowder factor optimization and cost trackingBlast vibration, flyrock, and wall damage dataLesson 3Cost and financial data: unit mining cost breakdown (labor, fuel, maintenance, blasting, contractor costs), cost per ton mined and per ton processed, and cash flow timingThis lesson breaks down cost and financial data for open pit mining, covering unit cost details for labour, fuel, maintenance, blasting, and contractors, plus cost per tonne mined or processed, and cash flow schedules, to tie operations to budgets and forecasts.
Cost centers and chart of accounts designUnit cost per ton mined and processedFuel, labor, and maintenance cost driversBlasting and contractor cost trackingCash flow timing and variance analysisLesson 4Production accounting and sampling: grade control sampling, assay variance, moisture measurement, and head grade vs reconciled gradeThis lesson explains production accounting and sampling data, including grade control, assay differences, moisture checks, and head grade against reconciled figures, for accurate metal tracking and meeting audit standards.
Sampling protocols and QA/QC controlsAssay variance, bias, and precision checksMoisture content and tonnage correctionsHead grade versus reconciled grade gapsMetal accounting balance and reportingLesson 5Haulage and cycle time analysis: fleet routes, empty/load times, fuel consumption, tire wear, and haul distance distributionsThis lesson details haulage and cycle time data for analysing truck routes, wait times, fuel use, tyre wear, and distance patterns, to optimise dispatch, cut bottlenecks, and lower running costs.
Cycle time breakdown and time stampsRoute geometry and haul distance profilesFuel consumption by route and payloadTire wear, TKPH, and road condition dataQueue time, spot time, and dispatch rulesLesson 6Equipment performance data: availability, utilization, mean time between failures (MTBF), mean time to repair (MTTR), and productivity by unitThis lesson focuses on equipment performance metrics for trucks, shovels, drills, and others, covering availability, utilisation, MTBF, MTTR, and output per unit, for better maintenance planning and benchmarking.
Time categories and delay coding standardsAvailability and utilization calculationsMTBF and MTTR data collection methodsComponent failure modes and historiesUnit productivity and benchmark dashboardsLesson 7Key operational metrics: material movement, production tonnage, strip ratio, grade control, and plant feed reconciliationThis lesson defines core metrics for open pit copper-gold mines like material moved, tonnage produced, strip ratio, grade control, and plant feed checks, for consistent reporting aligned with mine plans.
Material movement and mining rate trackingOre, waste, and stockpile tonnage dataStrip ratio monitoring and pit phase dataGrade control model versus mined gradesMine-to-mill plant feed reconciliationLesson 8Safety and workforce data: incident reports (TRIF/TRIFR), near misses, absenteeism, overtime, training records, and fatigue indicatorsThis lesson shows how to organise and analyse safety and workforce data for spotting risks, managing fatigue, boosting training, matching staff to production needs, and following Brazilian rules.
TRIF/TRIFR and severity rate trackingNear miss capture and root cause analysisAbsenteeism, overtime, and shift patternsFatigue risk indicators and mitigation plansSafety training records and competency gaps
