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Mining

Ore bodies, machines and assays held in one place.

A mine is a fleet problem and a geology problem at the same time: ore-body records describe what is underground, and a continuous stream describes how the machines are getting at it.

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From haul truck to grade report, through one data layer.

The story

From haul truck to grade report, through one data layer.

Where it starts

Fleet and plant telemetry

Cycle times, payloads, vibration and crusher throughput as measurements. It is the first of 4 workloads running in Mining.

The question it raises

Grade to throughput

Read assay results and plant measurements in one request rather than reconciling a laboratory system against a historian.

Why one question is hard

From Survey to Dispatch

Mining data moves through 4 stages — Survey → Extraction → Processing → Dispatch. The shapes in play are Time series, SQL, JSON / documents, Objects, Events, and answering one question means reading across all of them.

What PLOMID contributes

Mining data is dense in two directions at once: many machines, many measurements. These are the parts that keep the reads bounded.

  • Time-ordered storage Measurements and events are stored beside the records and documents they describe, so history and current state agree.
  • Predicates narrow the work Indexes and access paths decide what a query touches before a page is read, so operational reads stay bounded.
  • Deployment is a decision Self-hosted, edge and managed topologies are design destinations of the deployment fabric, and the fabric is specified as its own part of the platform.
The environment

Geological models, fleet telemetry, plant throughput and equipment history.

Geological models and survey records are documents and objects; haul fleet and plant sensors produce time-ordered measurements; production reporting leans on both. PLOMID keeps the measurements with the records they describe, so grade, throughput and equipment history are read from one place.

One environment · many workloads

What runs against mining data.

4 workload families over one set of shapes. Choose one to see what it moves and where it lands.

Cycle times, payloads, vibration and crusher throughput as measurements.

  • Planned once against the layer, not once per store
  • Read beside the records it shares a key with
  • Persisted under one storage contract
The data journey

How mining data reaches one layer.

Walk the path the data takes, from the environment that produces it to the questions it answers. Select a station, or a shape, to read each step.

From haul truck to grade report, through one data layer.

Environment

The site

Pit, plant and fleet, spread over terrain with an intermittent link to town.

Time series

Where the data goes to work

Questions the field asks daily.

Each one is a workload over the shapes above, answered from the same layer rather than from a purpose-built copy.

Grade to throughput

Read assay results and plant measurements in one request rather than reconciling a laboratory system against a historian.

  • SQL
  • JSON / documents

Component life

Component change-outs are records, vibration is a measurement, and both live together, so history is readable per machine.

  • Time series
  • Events

Delay accounting

Stoppage events sit beside the telemetry that shows them, which is what makes a delay report verifiable rather than claimed.

  • Time series
  • SQL

Remote site operation

A site can read the same layer as the head office, which removes the nightly extract that only ever lands sooner or later.

  • SQL
  • Objects
Data models in play

The shapes, in one layer.

5 shapes carry this domain. Choose a stage to read the operation, or a shape to see every stage that handles it.

PLOMID · Mining survey · extraction · processing · dispatch Select a stage
Stage

Survey

Drill results and assays as records and documents

SQL · JSON / documents

Workload map Mining workload map. Every shape on it is a surface of the layer, and each stage names the part of the operation it carries.
  • Time series Measurements and events in time order
  • SQL Records, keys and joins
  • JSON / documents Documents and nested objects
  • Objects Large assets with queryable metadata
  • Events Operational events as they happen
Workload architecture

Which workload touches which model.

The work, the shapes it names and the path a request takes — from the field to the control room.

Mining · workload architecture
Workloads

What runs against this data.

  • Fleet and plant telemetry
  • Geological and survey records
  • Equipment history
  • Production events
Data models

The shapes those workloads read and write.

  • Time series
  • SQL
  • JSON / documents
  • Objects
  • Events
The layer

One path from a request to the data it names.

  • Planning Predicates narrow the work before it runs
  • Execution Records, fields and windows answered together
  • Transactions Readers and writers do not block each other
Surfaces

How the work reaches the layer.

  • SQL surface The query language the layer is documented in
  • Applications Services and jobs writing and reading as they run
  • Analytics & AI clients The same layer, the same access path
Deployment & residency

Where this data is allowed to run.

Pit and plant sites lose connectivity, so reads have to survive an intermittent link to the central system.

Deployment, residency and control
What you build next

Digital Twins

An asset model that is read from operational data instead of synchronised with it.

If Grade to throughput is your question, start here.

See Digital Twins Every solution
Next

Where to go next

Solutions The workload answers this industry leans on, with their models and status. Platform The data models in the product today, and the ones extending the layer. Architecture How a request is planned, executed and persisted once it reaches the layer.