Knowledge of the site. The power of the decision.
In mining, every decision is shaped by interdependent data: geology, ore grade, production capacity, equipment, processes and economics. Gelecek Madencilik combines its focus on resource development with digital capabilities that assess these data within a shared decision-making environment.
Our aim is not to reduce complex operations to a single indicator, but to enable specialists to compare alternatives. We consider modelling, planning and monitoring tools in relation to site conditions and evaluate forecasts alongside actual outcomes.
- Resource evaluation
- Production and plant planning
- Fleet and maintenance analytics
- Process and economic scenarios
Bringing knowledge of the mine into operational decisions.
Geology, planning, metallurgy, finance and daily operations approach the same site with different questions. Our digital mining work brings these questions together through shared data and comparable scenarios.
Material flow from the quarry to industry.
Our experience in industrial raw material projects includes dolomite and quartzite production for the glass industry, overburden stripping and haulage. Extracting material and delivering it to the plant that uses it involve successive site and logistics requirements.
Dolomite work in Mersin during 1996–1999 is one example of quarry operations and industrial supply being planned together. This experience complements an approach that considers material, transport and plant requirements as interconnected parts of production.
From fragmented data to a shared workspace.
Information from sensors, geological models, historical records and operational applications is brought together in a common data structure. Cleaning, organisation, analysis and modelling steps are connected through visual workflows. Machine learning, time series forecasting and the digital twin approach support the examination of different operational scenarios using the same data.
Three-dimensional resource models, geographic information and remote sensing data are linked to grade control and the production plan. Connections with ERP, GIS and CAD systems aim to bring information held by teams in separate environments into the operation as a whole. Cloud, edge device and offline working options are evaluated with the site’s connectivity conditions in mind.
Seeing more than one future for a plan.
The mine plan is a working environment in which geology, equipment capacity, maintenance schedules and economic conditions are tested together. Pit limits and the sequence of block extraction are evaluated against production targets for each period. Traditional planning and direct block scheduling approaches make it possible to compare how different constraints affect the production profile.
Feasibility can be examined in greater detail when truck cycles, haul roads, fleet requirements, stockpile areas and waste movements are incorporated into the plan. The effects of changes in cut-off grade, production rate and mining sequence are analysed. Stockpiling, reclaiming and blending decisions jointly affect feed quality, rehandling and storage costs.
- Constraints
- Ore grade, stripping ratio, geotechnical conditions, equipment and plant capacity.
- Scenarios
- Alternatives for production sequence, fleet, haulage, stockpiles and blending.
- Decisions
- Production profile by period, resource requirements and economic comparison.
When production changes, the economics change too.
The physical production plan is linked to the financial model through metal prices, operating costs, taxes and obligations such as royalties. Different assumptions, including base prices, spot prices and market expectations, allow the effects of changing conditions on project economics to be examined.
Net present value, internal rate of return, free cash flow, payback period and all-in sustaining cost are different indicators of the same scenario. Traceability of inputs and calculation steps makes the assumptions behind results visible during budgeting, investment appraisal and model review.
Planning heap leaching together with production and the budget.
Heap leaching is evaluated through the relationship between the properties of the material placed, its recovery behaviour and production expectations over time. Kinetic models can be calibrated against actual operational data and rerun for different operating conditions. Heap inventory and material movements help determine stacking and leaching priorities.
Recovery forecasts, leach duration and reagent requirements are linked to budgeting and resource planning. In work on copper and gold applications, the aim is for metallurgy and finance teams to assess the same scenario together. The model’s relationship with the mine plan and detailed operational records support retrospective review of results.
Making uncertainty visible rather than concealing it.
The resource model is compared with grade control data from the site to examine differences between planned material and actual production. Models supported by historical records and current observations make ore grade estimates, ore–waste boundaries and low-confidence areas visible.
This information helps geologists identify areas requiring reassessment and helps planning teams account for uncertainty in sampling and excavation decisions. Reconciliation of planned and actual results and performance reports show where estimates are becoming more robust or require new observations.
Understanding the site’s daily rhythm.
Weekly maintenance indicators, real-time mechanical availability and unplanned downtime form a shared decision-making area for maintenance and operations teams. Recurring failures, load and overload indicators, travel times and equipment status are evaluated together. Historical data is used to forecast expected downtime and potential upcoming failures.
Fleet records make it possible to examine truck queues, haulage cycles and material movements during shifts. Comparing active, idle and maintenance time reveals where delays occur. Stockpile composition and incoming and outgoing movements provide a combined view of available material and plant feed requirements.
Measuring the environment around the operation.
Water truck route and usage data can be linked to dust control planning. Fuel consumption and fleet emissions indicators are considered alongside external environmental data to examine how water, energy and environmental conditions relate to operations.
Monitoring waste storage and water movements, occupational safety observations, and personnel and shift planning are also part of digital operations. Training scenarios developed with virtual and augmented reality form a separate area of work that supports team preparedness.
Making knowledge work across teams.
Operational documents, spreadsheets and databases provide a knowledge context for artificial intelligence assistants that answer teams’ everyday questions. Access organised by department and role, multilingual questions and answers, and task workflows are considered across functions such as finance, human resources and procurement. Usage and feedback data support the development of this way of working.
The digital solutions ecosystem aims to support the discovery and comparison of applications and models and their connection to existing workflows. Technical publications, training, webinars and exchanges of expertise complement practical knowledge. Experience in mine planning, operations, financial modelling and geospatial analysis comes together through a network of expertise spanning North America, Europe and Türkiye.
Each specialism focuses on a different decision.
We evaluate digital solutions not only by technology names, but also by the information they use and the decisions they support.
| Area of work | Information used | Decision supported |
|---|---|---|
| Geology and grade control | Resource model, sampling and actual production | Ore–waste boundaries, confidence levels and reassessment priorities. |
| Mine planning | Block model, capacity, maintenance and haulage constraints | Production sequence, fleet requirements, stockpiles and blending. |
| Metallurgy | Heap inventory, kinetic data and operational observations | Leaching priorities, recovery forecasts and reagent budget. |
| Finance and investment | Production, price, cost and tax assumptions | Cash flow, net present value, payback and sensitivity. |
| Maintenance and operations | Failure, equipment status, queue and shift records | Maintenance priorities, time utilisation and material flow. |
| Environment and resource management | Water, fuel, routes and environmental observations | Monitoring resource use and planning it together with operations. |
Expertise in detail.
Geology, resources and ore grade data
We focus on establishing a traceable data link between geological knowledge and production decisions.
- Three-dimensional geological models, GIS and remote sensing data.
- Comparison of resource and grade control models; reconciliation of planned and actual results.
- Assessment of ore–waste boundaries and areas of uncertainty through maps and analyses.
Strategic production planning
A production plan is shaped by economic and operational constraints as well as the site’s geology. We work with tools that assess alternative scenarios together.
- Pit limit optimisation and block scheduling.
- Short- and long-term targets based on equipment, maintenance and plant capacity.
- Truck cycles, haul road modelling, stockpiling and blending scenarios.
Heap leaching and process modelling
Understanding material behaviour and how the process develops over time supports adaptation of the plan to the site.
- Kinetic recovery models and calibration against actual data.
- Scenarios for leach duration, reagents, stockpiles and material movement.
- Linking process outputs with the production plan and economic assessment.
Fleet, maintenance and material flow
We evaluate equipment performance within the daily rhythm of production, focusing on analyses that reveal where operations lose time and capacity.
- Mechanical availability, maintenance indicators and causes of unplanned downtime.
- Equipment health, failure prediction and queue time analyses.
- Support for real-time fleet tracking, task allocation and route planning.
- Shift and time utilisation; reporting on stockpiles, feed and material movement.
- Joint evaluation of supplier performance, logistics flows and inventory data.
Economic modelling linked to production
We examine the economic implications of a technical plan through models with explicit, adjustable assumptions.
- Linking production data to scenarios for revenue, costs, metal prices, taxes and royalties.
- Assessment of net present value, internal rate of return, cash flow, payback and all-in sustaining cost (AISC).
- Sensitivity analysis, performance dashboards and traceable model records.
Data platform and digital operations
Data from different systems working on a common basis makes it easier to bring analyses into everyday use.
- API and IoT connections; data validation and no-code analytical workflows.
- Data connections with enterprise resource planning (ERP), geographic information (GIS) and computer-aided design (CAD) systems.
- Natural-language scenario creation, filtering and automation of recurring analytical workflows.
- Digital twins, interactive visualisation and time series forecasts.
- Cloud, local processing and offline use options according to the site’s connectivity conditions.
Resource use and environmental monitoring
Operational data is also a starting point for understanding resource consumption.
- Monitoring water and fuel use alongside routes and operating time.
- Fleet emissions indicators and environmental reporting support.
- Monitoring data on tailings and water resources, with support for risk assessment and reporting.
- Operational analyses of watering, stockpile areas and continuity of feed.
Site safety and team preparedness
We consider digital operations together with on-site teams’ preparedness and daily working arrangements.
- Digital tools that support the monitoring of hazard indicators.
- Shift and personnel scheduling; aligning team plans with operations.
- VR/AR-based training simulations and scenario exercises.
A solutions and knowledge ecosystem
We develop platform approaches that bring mining-specific software, artificial intelligence models and expert knowledge together in the same digital environment.
- Discovering, evaluating and testing applications and models from different providers, and connecting them to workflows.
- Knowledge sharing through technical publications, articles, videos and webinars.
- Extending existing analyses with new tools and supporting learning among specialists.
Different expertise,
a shared future.
Let’s take the next step
together.
Share your project, requirements or collaboration proposal for Gelecek Madencilik with us.