MiningIQ Platform Capabilities — Technical Specifications and Features
A complete technical reference for IMC Mining's MiningIQ platform and MineCost engine — covering every module from drillhole database management through to enterprise financial modelling. Updated April 2026.
Platform Overview
MiningIQ connects every stage of a mining feasibility study in a single secure web application. MineCost calculates operating and capital costs from first principles. Together they eliminate manual spreadsheet handoffs — every data point is traceable from source to output.
Platform Modules
Eight integrated modules covering the complete mine study workflow.
Drillhole Database & QA/QC
Import, validate, and manage collar, survey, assay, and lithology data. Multi-element support with automated QA/QC checks.
Block Model Analysis
Import from all major formats. Interactive grade-tonnage curves, histograms, and configurable dashboards.
Pit Optimisation
Pseudoflow (Hochbaum) for pit shell generation. Parametric revenue factor shells with category-based ore classification.
Schedule Optimisation
Bienstock-Zuckerberg LP with sliding-window MILP refinement. Multi-constraint scheduling with ore-density-first integer repair.
Haulage Simulation
Discrete event simulation (DES) with first-principles physics — manufacturer rimpull curves, per-segment grade, rolling resistance, and speed modelling.
MineCost — Zero-Based Costing
First-principles: fleet, manning, consumables, WBS-level opex + capex. Direct integration with schedule outputs.
Drillhole Database Management & QA/QC
- Import collar, survey, assay, and lithology data from CSV, databases, or legacy formats
- Multi-element assay support with per-project configuration
- Automated QA/QC: duplicate analysis, standard reference checks, blank analysis
- Drillhole visualisation and data exploration dashboards
- Full audit trail for all imports and modifications
Block Model Analysis
- Import block models from all major formats
- Interactive grade-tonnage curves and histogram analysis
- Configurable dashboards with chart types, weighting, and cutoff controls
- Sub-blocked and regular block model support
Pit Optimisation
- Pseudoflow algorithm (Hochbaum) for maximum-flow pit shell generation
- Parametric revenue factor shells for nested pit analysis
- Category-based ore/waste classification
- Multi-element revenue calculations
- Interactive pit shell visualisation and comparison
Mine Schedule Optimisation
- Bienstock-Zuckerberg (BZ) linear programming formulation
- Sliding-window MILP post-processor
- Greedy forward-pass integer repair with ore-density-first ordering
- Topological precedence enforcement across stages and benches
- Configurable constraints: mining cap, mill cap, ore/waste ratios, blending
- Multi-price-deck scenario analysis
Haulage Simulation (DES + First-Principles Physics)
- Discrete event simulation with first-principles physics using manufacturer rimpull curves
- Segment-by-segment road modelling: grade, rolling resistance, speed limits
- Automatic route generation using shortest-path graph algorithms
- Multiple truck types with payload and empty-weight specs
- Validated against operational data across multiple mine sites
MineCost — Zero-Based Cost Modelling
- First-principles cost from physical drivers
- Equipment fleet: size, count, availability, utilisation, productivity
- Manning: roster patterns, crew sizes, labour rates by role
- Consumables: fuel, tyres, GET, explosives, wear parts
- WBS-level operating cost breakdown
- Capital scheduling: pre-production, sustaining, closure
- Direct integration with MiningIQ schedule outputs
Enterprise Financial Modelling
- NPV, IRR, and payback period
- Multi-price-deck scenario analysis
- NPV waterfall analysis
- Risk-adjusted DCF modelling
- Multi-metal, multi-process revenue streams
- Period-by-period cash flow with tax, royalty, depreciation
Study Team Collaboration
- Document storage with AI-powered full-text indexing and search
- Kanban boards for task management
- Meeting interfaces for coordination
- Role-based access controls per project
- Complete audit trail
Private AI & Deployment
- Private LLM deployment — no data leaves your infrastructure
- AI-assisted document review, data extraction, technical writing
- Secure web app — browser-based, no desktop install
- Private cloud with dedicated resources per client
- Encrypted document storage
MiningIQ by the Numbers
Frequently Asked Questions
What algorithm does MiningIQ use for pit optimisation?
Pseudoflow (Hochbaum) for maximum-flow pit shell generation, producing nested shells across revenue factors.
What algorithm does MiningIQ use for scheduling?
BZ linear programming, then greedy forward-pass integer repair with ore-density-first ordering, plus optional sliding-window MILP refinement.
How does MiningIQ model haulage?
MiningIQ combines discrete event simulation (DES) with first-principles physics from manufacturer rimpull curves. Each road segment has grade, rolling resistance, and speed limits. Routes generated via graph algorithms. The DES engine models equipment interactions and fleet productivity.
What is zero-based cost modelling?
Every cost built from physical drivers — equipment hours, fuel burn, tyre life, manning — rather than historical averages. MineCost produces WBS-level opex and capex.
Can MiningIQ handle multi-metal deposits?
Yes — multi-element assay data, multi-metal revenue in pit optimisation, and multi-metal revenue streams in financial modelling. Each metal gets its own price deck and recovery.
Is MiningIQ suitable for feasibility studies?
Specifically designed for scoping through DFS — covering the complete workflow with study collaboration tools built in.