Mine planning: engineering, mining law and AI for efficient mining

Mine planning is a business decision

Mine planning connects geology, engineering, operations, licensing, contracts, investment and the market. It organizes the extraction sequence, anticipates constraints and shows how today's choices affect safety, resource recovery, costs and the life of the operation.

In an episode of the Direito Minerário channel, attorney André Alves Cunha talks with mining engineers Filipe Ciscato and Rodrigo Cordova about this integration. The central idea is straightforward: planning is not a document prepared only to complete a stage. It is the basis for deciding what to do, when to do it and which risks must be addressed before capital and people are mobilized.

Why small and medium-sized mining companies must plan early

Smaller operations often work with lean teams, more sensitive cash flow and little room to correct implementation decisions. This makes planning even more important. A poorly positioned face, a plant that is incompatible with the ore or a sequence that brings waste forward and delays revenue can jeopardize the entire project.

Planning should begin when the first geological data already supports scenario building, not only when the operation is ready to start. At this stage, alternatives can still be compared, assumptions reviewed and the technical project aligned with legal and environmental obligations.

• Transform geological data into production and material-movement scenarios
• Check compatibility among the mine, plant, access routes and infrastructure
• Anticipate licenses, mineral rights, contracts and conditions
• Test economic sensitivity before committing investments
• Define controls for uncertainties that cannot yet be eliminated

The valley of death between project and operation

One topic discussed in the video is the implementation valley of death: the period when the venture has already consumed significant resources but has not yet achieved stable production and cash generation. At this stage, incompatibilities among the geological model, pit geometry, plant capacity and schedule become especially dangerous.

Planning reduces this risk by establishing a traceable decision path. Assumptions, scenarios and limits must be explicit. Management can then distinguish which results depend on confirmed information and which still carry uncertainty.

A case of savings associated with sound planning

The discussion presents a practical case in which a planning review was associated with estimated savings of BRL 60 million. The amount is specific to that project and should not be generalized, but it illustrates the scale a sound engineering decision can reach before material movement even begins.

The benefit does not come from a single formula. It results from better data interpretation, sequence selection, coordination across project areas and the prevention of investments that would later need to be redone. Comparing scenarios usually costs far less than correcting a flawed implementation.

Where artificial intelligence can help

Artificial intelligence can accelerate data organization, scenario comparison, inconsistency detection and analysis preparation. It can also make tools that once required highly fragmented workflows more accessible. However, AI does not replace technical responsibility or solve poor input data on its own.

The engineer remains responsible for validating assumptions, understanding the deposit, recognizing limitations and explaining why an alternative is appropriate. The best use of AI is to expand the professional's analytical capacity while preserving traceability and technical judgment.

Planning is a compass, not a rail

A mine changes as new drilling, reconciliation, cost, productivity and geotechnical-behavior data becomes available. The plan cannot therefore be treated as an immutable rail. It should guide the operation while being updated whenever reality moves away from its assumptions.

CCMENG works in mine planning, geology and geotechnics to transform field data into auditable decisions. The goal is not to promise an absence of uncertainty, but to make uncertainty visible and manageable.