Mineral Processing Plant and Concentrator Operations
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Predictive asset decisions: know when mining equipment must stop

The prediction is about the asset. The intervention is about the mine. Predictive maintenance becomes a timing decision.
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Imagine a haul truck whose condition data shows a drivetrain component beginning to degrade. The truck is still hauling. The component has not failed.
WHY THIS "PREDICTIVE ASSET DECISIONS" CHALLENGE?
A model may be confident intervention will be needed. But when should the mine actually take the truck out of production?

Stopping immediately may surrender capacity in a critical period. Waiting may preserve tonnes but narrow the maintenance window or leave the operation exposed if the condition accelerates.

Key benefits
What a predictive signal enables when it opens a real window

A predictive signal creates value when it opens a window in which the mine still has several acceptable choices.

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Several acceptable choices instead of one forced stop

The mine can keep the truck in service for a defined period, move it to less critical work or rotate another unit into the haul plan.

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Maintenance brought forward with parts and labor staged

Maintenance can be brought forward with the component and labor staged, aligned with a production window that reduces disruption.

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No asset run as long as possible, none stopped too early

The objective is not to keep a degrading asset running as long as possible. Nor is it to stop every asset at the first warning.

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The least damaging intervention chosen with foresight

Foresight is used while there is still time to choose the least damaging intervention for the operation, within safety limits.

How NTT DATA helps

01
Represent degradation as it evolves

Combine condition monitoring, historian data and asset-health models to show how the component condition is changing, not only whether an alarm fired.

Reliability engineer inspecting a haul truck drivetrain sensor
02
Put the asset inside the production plan

Connect the emerging condition to dispatch, fleet availability, haulage commitments and the work the truck is expected to carry before the likely intervention.

Haul truck fleet moving through an open-pit production plan
03
Expose the real maintenance window

Bring together engineering limits, production exposure, fleet redundancy, spares, labor and workshop capacity to find when intervention is feasible.

Maintenance team preparing a drivetrain and service bay
04
Compare permissible alternatives

Simulation, optimization or decision support can compare continuing, rotating the asset, changing its duty or bringing maintenance forward.

Mine planners comparing haul routes on a physical pit model
05
Commit the intervention across functions

Once the timing is chosen, propagate the decision into dispatch, maintenance planning, inventory and execution workflows so the mine acts on one coordinated plan.

Cross-functional mining team coordinating an intervention plan
06
Learn from teardown and result

Compare predicted degradation with the condition found in maintenance, the timing chosen and the production consequence, then refine the logic.

Engineers measuring drivetrain wear during teardown analysis
Planned haul truck intervention with production continuing across the mine
Proven impact
An early warning becomes useful when it creates notice to prepare and choose an intervention window

The mechanism is broader than prediction accuracy. The mine also needs the decision architecture that connects asset condition to production commitments, maintenance readiness and remaining alternatives.

Results that matter
Taking the asset out of service at a moment the mine chooses

A mature predictive capability should not be judged only by how many failures it anticipates.

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The mine chooses the moment, before the asset chooses it

Assets are taken out of service at a moment the operation has deliberately chosen, before the asset chooses the moment instead.

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The asset is managed inside the production plan, not apart

The emerging condition is connected to dispatch, fleet availability, haulage commitments and the work the truck is expected to carry.

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Dispatch, maintenance and inventory act on one plan

Once timing is chosen, the decision reaches dispatch, maintenance planning, inventory and execution so the mine acts on one plan.

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Each teardown improves the model and the intervention logic

Comparing prediction with what maintenance found improves both the model and the intervention logic for the next degrading asset.

Know when your mining equipment should stop

Explore how connecting asset health to production, fleet and workshop context can turn predictions into well-timed interventions.

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