Webinar: Reaching operational goals with K-MINE: Scheduling

Welcome to the K-MINE webinar on production scheduling for open pit mining. In this session, Anya (Business Development Manager) and Vitaly Drozdov (Senior Mining Engineer at K-MINE) demonstrate the updated scheduling module and walk through practical scenarios for building mid-term production schedules.

K-MINE covers the full mining cycle from exploration to production, with dedicated modules for both open pit and underground operations. Today's focus is on the scheduling module for open pit mine planning.

Mine planning optimizes the development of mineral reserves so the enterprise can maximize surplus value aligned with strategic goals. All planning activities are directed toward finding the best design and the best production schedule, accounting for capital investment, operational costs, revenue forecasting, and cash flow management.

Planning goals can be divided into three groups:

Open pit goals include maximization of performance, net present value (NPV), and extraction with minimum production costs, minimum waste extraction, and optimal transportation distances. There must also be a balance between ore and waste extraction, and between pit slope angles and economic indicators.

Mining equipment goals include optimized equipment repair plans, proper determination of optimal equipment life cycle, and maximization of technical availability, utilization rate, and efficiency of repair services.

Processing plant goals include boosting plant efficiency with minimum waste and minimum processing costs, maintaining constant ore flow, and ensuring the plant can respond promptly to changes in ore quality.

The planning process starts with strategic long-term planning, which defines goals and opportunities. It then moves to mid-term planning, which typically covers a five-year period and focuses on finding ways to reach the strategy defined in the previous stage. Finally, short-term planning covers up to two years and determines specific tasks for each piece of equipment, broken down by shifts.

Each stage inherits digital information from the previous one - surfaces, lines, tabular data on rock types, excavation volumes, and quality specifications. Today's webinar focuses on mid-term planning and how to achieve expected results using K-MINE's scheduling module.

Mid-term planning typically covers up to 5 years, though this depends on deposit size - shorter for small deposits, up to 10 years for large ones. The foundation for this phase comes from the life-of-mine (LOM) plan.

Mining direction is determined by surfaces from the LOM periods. The same pushbacks from the previous scheduling stage can be used. The block model should include sample results from exploration data. Scheduling calendars follow the same direction as the LOM plan but are enriched with clarifications on excavation capabilities, loading and transportation equipment, drilling equipment, excavator placement in mining areas, and pit sinking opportunities.

Mid-term planning also marks the start of detailed transportation calculations - main roads, loading and unloading points, rolling stock speeds - and identifies whether there is a lag or excess of equipment. This process is generally called a truck study.

The demonstration uses artificial data created specifically for this webinar: a block model with regular block size of 10 x 10 x 10 meters, iron ore as the mineral, with quality indicators of ferrum total and ferrum concentrate.

Rock classification: - Rock code 2: high-grade ore (located in the center of the open pit) - Rock code 4: low-grade ore (located closer to the western pit wall) - All other rocks: waste

Total rock mass to be scheduled: approximately 49.5 million tons, comprising 9.4 Mt of high-grade ore, 8.4 Mt of low-grade ore, and 31.7 Mt of waste.

The first scenario demonstrates how excavation volumes react when there is only one planning section. A single section is defined interactively by selecting block boundaries on screen. The scheduling intervals are set as one-year periods over five years.

Target indicators: 2 million tons of high-grade ore per interval, with a tolerance of 200,000 tons (10%). The software stops searching when high-grade ore reaches 1.8 million tons.

The initial result shows mining starting from the top with no sequence violations. Total rock mass is about 6.5 million tons with 1.8 million tons of ore. However, the total rock mass volume is highly variable - peaking in the second and fifth periods. This happens because the algorithm focuses on ore extraction first, providing minimum waste in early periods and accumulating a "waste debt" that peaks in the last period.

This uneven distribution is not feasible for operations: running equipment at 50% capacity in one period and 150% in another requires additional equipment and contractors.

To balance volumes, the waste transportation target is increased to approximately 10 million tons of total rock mass per period. After adjustment, the results show 9.5 Mt in the first period and more evenly distributed volumes across periods - though the fifth period still drops to 9.3 Mt total rock mass and only 0.9 Mt of high-grade ore due to depletion.

The volume of transported low-grade ore increases as the pit deepens, since the pushback bottom is oriented toward this ore type.

The second scenario uses K-MINE's built-in splitting tool to divide available blocks into four arbitrary sections (north and south at various elevations). This tool is useful for dividing work areas between several pieces of equipment within a single pushback and is much faster than building individual pushbacks.

Sections are split by vertical lines. Target indicators remain the same but without qualitative indicators.

Result: the expected even distribution was achieved in only two periods. Splitting into more sections did not provide a beneficial outcome in this case. The uneven distribution is caused by transport berms at each level, which gradually increase rock mass volume as mining deepens. Comparing both scenarios shows that additional sections are not always necessary to achieve balanced scheduling.

The third scenario represents the most common and correct approach to defining scheduling sections. It requires pre-prepared pushbacks from the mine design stage.

Three pushbacks are loaded from the block model using the pushback attribute. Target indicators: 1.8 million tons of high-grade ore and up to 9 million tons of total rock mass per period, plus a waste transportation target of 8 million tons with high deviation allowance.

When target indicators alone are not sufficient, force slots are applied to individual pushbacks. This method ensures that reaching each mining position is physically possible, since it is based on actual previously designed mining surfaces.

Result: with properly drawn pushbacks, the charts show even distribution of volumes across all periods. The schedule is feasible and ready for equipment assignment.

The scheduling module's optimization algorithm searches for optimal solutions efficiently and can be used for both short-term and long-term planning periods. The three scenarios demonstrate a clear progression: - Single section provides the fastest preliminary estimate - Split sections help divide work between equipment but may not improve balance - Pushback-based scheduling produces the most accurate and feasible results

The most important planning task is to define the optimal balance between ore and waste indicators - and K-MINE's scheduling module provides the tools to test multiple approaches quickly.

How accurate is the developed plan compared to actual operations? The plan corresponds as closely as possible to the conditions at the start of the planning period. During operations, unplanned mining activities may occur. When initial data changes significantly, it is better to revise the plan.

How to optimize the final pit and maximize overall NPV? NPV optimization is most important at the strategic long-term planning stage. K-MINE's Pit Optimizer module allows users to consider different final contour options with adjusted price factors. For details, see the previous webinar on Pit Optimizer capabilities.

What solver does K-MINE scheduling use? The solver creates specific relationships between blocks before starting calculations. During the search process, it identifies the single best solution for the mining sequence - essentially searching for the optimal extraction order based on defined constraints and target indicators.