M821V1 computes a mining schedule based upon the input data using the following steps:
1. The pit reserves are read and regrouped in up to twelve (12) M821V1 classes.
These classes include two waste classes (M821V1 codes 11 and 12) and ten (10) ore classes (M821V1 codes 1-10).
2. For each production period, the “ore” materials are summarized into eight (8) production classes: waste class 1, Type1 mill feed, mid, low and sub-grade stockpiles, Type2 mill feed, high-grade leach, and low-grade leach materials.
Waste classes 1 and 2 are based upon M821V1 codes 11 and 12. The separation of M821V1 ore classes into eight (8) scheduling categories is based upon the
specification of which of the ten (10) ore classes are to be mapped into one of the eight (8) scheduling categories for each period. This allows the cutoff grade to vary by production period.
The scheduling process consists of four major components. They are:
a) Find a feasible mining pattern that meets the production targets and operating constraints by systematically examining all the possible mining pushbacks and benches.
b) Compute the usage of dumps, trucks and shovels via simulation of the removal of the mined materials in step 1 so that the availability of dumps, trucks and shovels are not violated.
c) Calculate the operating costs and revenues for the feasible mining solution which meets the requirements of both steps a and b.
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d) Choose an “optimum” mining solution based on the chosen objective among all the feasible mining solutions.
3. A feasible mining pattern (mining layouts) is determined by examining all combinations among all the pushbacks and benches working in one period. The program searches the feasible mining patterns in following fashion:
a) Sort all pushbacks according to economics so the pushback with the highest ratio of NPV over its total tons is on the top of the mining order list and the pushback with the lowest at the bottom.
b) Adjust the pushback list by precedence requirements so the mining order agrees with both the economics and the precedence constraints.
c) Pick up k pushbacks that work in the current period according to the pushback mining order and the permutation sequence. For k pushbacks out of n pushbacks working, there is a total of [n!/{(n-k)!k!}] permutations. Many of them can be dropped because of violating precedence constraints or mining targets.
d) Locate the bottom benches in each pushback based on pushback and bench mining rate.
e) Check among all the combinations of k pushbacks for feasible mining patterns.
A feasible mining pattern consists of i pushbacks (i #†k). Inside each of the I pushbacks, there are m(i) benches mined. Of the m(i) benches, the m(i)-j>0 are the base benches, and the j benches below (m(i)-j) benches are the bottom benches.
All the m(i)-j base benches are completely mined. The j bottom benches are mined in fractions via linear programming with the status of direct mill feed stockpiles considered automatically. The “ore” and “waste” may be mined in different fractions on the bottom benches. Of the j bottom benches in the same pushback, the total mining on an upper bench is greater than on a lower bench. A feasible mining pattern is illustrated on page 821-4.
Whenever a feasible mining pattern is found, the usage of dumps, trucks &
shovels and the economics are calculated. A feasible solution is defined as a feasible mining pattern that also passes the destination, truck and shovel availability check. The economics are calculated for each feasible solution.
Each feasible solution is a candidate to be the optimum solution for current period. During the solution enumeration, if the number of feasible solutions exceeds a pre-defined limit, the search is stopped and the program moves to step g.
f) All combinations of benches of k pushbacks are examined. If not all the permutations of k out of n pushbacks are evaluated, go to step c for next permutation. Otherwise, check if at least one feasible solution was found. If no feasible solution was found, go to step h. If at least one feasible solution was found, continue.
g) Exit with at least one feasible solution.
h) Exit with no feasible solution.
Throughout the feasible mining pattern search, an audit trail is provided by choice, so
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4. Once a feasible mining pattern is found, the displacement of the required ore and waste materials is simulated for a truck and shovel operation. The objective is to see if the ore and the waste intended to be mined can actually be loaded and transported to the appropriate destinations. The simulation progresses as follows:a) Pick up a pushback from the mined pushback list.
b) Determine the amount of ore or waste that needs to be removed.
c) Find a destination (lift) based on the shortest distance, the permitted connection and the available physical, period, and spread dumping capacity. If there is no viable destination, go to step i.
d) Find a “loader” with available hours from the loader list in a top to bottom fashion.
The “loader” could have multiple units with the same characteristics, such as the loading cycle, the availability, the percent of use and the operating costs. If there are no “loader” hours available, go to step i.
e) Find a “truck with available hours from the truck list also in a top to bottom fashion. The “truck” selected could have multiple units with the same haulage cycle, availability, the percent of use and the operating costs. If there are no “truck”
hours available, go to step i.
f) Set the amount of ore or waste to the minimum of the amount permitted by steps c, d, and e. Update the usage of destinations, trucks and shovels.
g) Check if all the materials of step b are removed. If not, go to step b. If yes, check if all the “mined” materials from all the pushbacks are removed. If not, go to step a. If yes, continue.
h) The feasible mining pattern is a feasible solution. Hence, exit to calculate the costs and revenues for this feasible solution.
i) Error exit. The feasible mining pattern under evaluation is dropped. An audit trail is provided by choice to examine why the solution was infeasible.
Special rules added to the simulation:
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Available hours and operating costs of trucks & shovels can be changed among four distinct time spans to reflect the equipment at different ages.•
Spread dumping to simulate the actual haulage and dumping environment. The spread dumping is based on a pre-defined dumping rate for each destination. In other words, if a closer destination A reached its spread dumping capacity, the material has to go to a destination B further away with spread dumping capacity.Only after all the destinations with connections reached their respective spread dumping capacities, can the materials be dumped on destination A again in any one period.
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A destination may be specified as available or non-available or must be dumped to up to a pre-defined period.•
Multiple material types (e.g., ore, waste, stockpile and so forth) can be sent to distinct destinations.Proprietary Information of Mintec, inc. M821V1 Summary
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5. After a feasible solution is determined, the shovel loading hours and the truck haulage hours are available. The operating costs for trucks and shovels are calculated. Based on which ore destination the ore materials are sent to, different recoveries and processing costs are used. With “fixed” mining costs added, the overall revenues and costs are calculated. The net cash value from the feasible solution is obtained. In the developed method, no taxation is considered.
6. As an alternative; the materials mined from all pushbacks can be allocated to available material destinations by linear programming on a pushback to destination basis. The materials on each bench are then allocated to individual lifts based on LP results using more detailed cycle times.
7. Twelve criteria are set up to filter all the feasible mining solutions. They are the maximization and minimization of the following six items:
net value
primary mineral content stripping ratio
haulage and loading cost haulage hours
exposed ore
At the end of the solution enumeration for any one period, one feasible solution, which fits into the period objective, usually, maximum net value, would be selected to be the period “optimum” solution.
This process of locating feasible mining patterns, computing the use of dumps, trucks
& shovels, calculating the economics, filtering the feasible solutions based on the 12 criteria, and selecting the “optimum” solution, continues one period at a time until all the periods are sequenced.
Re-running, based on the mining solutions obtained from previous periods, can alter a mining sequence in order to examine more scenarios. The cutoffs can be changed from period to period to enhance the mine NPV.
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