جستجوی مقالات مرتبط با کلیدواژه "ارزش خالص فعلی" در نشریات گروه "مهندسی معدن"

Production planning in underground mines is still a manual process and there are no suitable tools for optimal production planning for these mines. It is impossible to achieve a real optimum result through manual programming because of the complexity of underground mines and production planning problems in these mines. Due to the increasing consumption of minerals on one hand and the depth of mineral reserves, on the other hand, efforts to achieve comprehensive production planning optimization methods in underground mines and especially large-scale production methods with high production rates are inevitable. Among the underground mining methods, sublevel caving is a common method for hard rock mining, and there are very few studies of long-term production planning for this method. In this paper, a new mathematical model with the aim of maximizing the net present value (NPV) is presented to optimize the production planning of the sublevel caving method. The technical and operational constraints of the sublevel caving method such as development constraints, production capacity, sublevels geometry, and storage access are included in this model. The proposed model was implemented on an economic block model and the maximum NPV was determined. A comparison of the results obtained with the results of manual planning shows a significant increase in NPV mining operations.

SummaryThe aim of this paper is to present a new algorithm to determine ultimate pit outline and mining sequence simultaneously based on the maximization of the net present value (NPV). For this purpose, a nonlinear binary mathematical model was established and then a heuristic algorithm was developed to solve this NP-Hard problem. IntroductionThe ultimate pit limit is an important problem which is determined by maximization of undiscounted profit or NPV. The floating cone algorithm and its modified versions, Korobov algorithm, Lerchs-Grossman method and maximal flow algorithm were developed to generate ultimate pit limit based on the maximization of the undiscounted profit. Nevertheless, it is better to determine the pit outline based on the maximization of NPV. To achieve this goal some algorithms like Wang-Sevim, Latorre-Golosinski and Roman were established.Methodology and ApproachesThe binary and nonlinear mathematical model to determine the ultimate pit limit on the basis of maximizing NPV and a few suggestions for its linearization were presented. Afterwards, by defining the concepts of downward cone, positional weight and nearest ore index, a heuristic algorithm was developed to determine the ultimate pit limit and mining sequence all together.Results and ConclusionsThe algorithm was applied for 2D and 3D block models and the results showed that it is able to produce optimum outcome. Complexity of the algorithm is low and easy to use and as well as for education purpose. It is also able to consider variable slopes and grade-based constraints for production planning in the algorithm.

Determining the transition limit from the open pit mining to an underground mining method is one of the key decisions where there is the possibility to mine using both open pit and underground mining methods. Transition level is a depth where open pit mining is the best choice above this depth and underground mining is prioritized below it regarding the technical and economic aspects. In the early-stage mine planning studies, including the determination of transition limit, simplicity, practicality, and quickness of decision making are of the requirements, while achieving the acceptable answers is regarded. In this research, a practical approach based on combining Lerchs and Grossman algorithm and the Equilibrium Stripping Ratio (ESR) method is proposed to determine the transition limit. For this purpose, firstly nested and developing pits are generated with the objective of maximizing the net present value (NPV), then the Incremental Stripping Ratios (ISR) of each of these optimal developing pits are calculated. According to the alternative underground mining method(s), the ESR is calculated and finally, the transition limit will be determined comparing the ISR of these developing pits and the calculated ESR. In the present research, this approach is applied to determine the transition level in an iron ore deposit. To verify the determined transition limit, calculating the cumulative net present value shows that mining by underground method below the determined transition level can increase the NPV by 23% compared to continuing open pit mining.

Uncertainties of economic parameters have an indispensable role in mining evaluation projects. Therefore, evaluation of a mining project without considering the available uncertainties is incorrect and unreliable. Metal price uncertainty is the most important parameter in a mine economic uncertainty. Many researchers have studied the role of economic uncertainties in the production planning. But majority of these studies are conducted in one-element deposits and the two-element deposits are rarely investigated. In this research the binomial tree technique valuation is used to compute the production planning evaluation in two element deposits for price uncertainty. It is concluded that the mine evaluation suggests greater net present value when price uncertainty is considered for both element. 

The main sources of uncertainty arising at the beginning of a mine project can be categorized into three groups: geology uncertainties, engineering uncertainties and economic uncertainties. Many researchers studied these types of uncertainties. In majority of the aforementioned researches, price uncertainty effect was investigated only for one- element deposits, which can result in an inaccurate valuation. Therefore, in this paper, the binomial tree method was used for determining the effect of price uncertainty in valuation of two-element deposits. 

In this research the binomial tree technique valuation is used to compute the production planning evaluation in two element deposits for price uncertainty in four scenarios: Assuming price certainty for both elements; assuming price uncertainty for first element and price certainty for second element; assuming price certainty for first element and price uncertainty for second element; assuming price uncertainty for both elements. 

It is concluded that the mine evaluation suggests least NPV of 245.05 thousand dollars when price certainty is considered for both elements and greater NPV of 349.6 thousand dollars when price uncertainty is considered for both elements. The sensitivity analysis showed that even by changing input economic parameters, the NPV, which was computed in price uncertain for both elements, was the greatest.

Summary :Mining production planning is a very vital subject of mine design process. One of the most important issues in mine production planning is the cutoff grade which is simply a grade used to distinguish between ore and waste. Waste materials may either be left in place or sent to waste dump. Ore is sent to the mill for further processing. Lower cutoff grade causes higher amounts of ore to be processed and subsequently lower amounts of waste materials to be dumped resulted in fluctuations in the cash flow of a mining project. The main goal of the long-term production planning is to determine strategies to implement the cutoff grade and short-term production planning. One of the most important aspects of mine design is to determine the optimum cutoff grade. The optimum cutoff grade leads to maximize the profit or the Net Present Value (NPV). Maximizing of NPV is a non-liner programing problem that has been considered in the recent decades. The main factors involved in the Lane algorithm are the capacities of each part of the mine (e.g. extraction capacity of mine, refinery plant, and market), time value of currency and distribution grad of deposit. Since Lane algorithm calculation steps are very time consuming, In this study a novel technique namely Imperialism Competitive Algorithm (ICA) is used to determine the optimum cut-off grade. The results show that optimum cut-off grade obtained by ICA is more accurate and faster than other simulation algorithms. In this paper a novel optimization algorithm based on imperialist competitive algorithm (ICA) is used to determine the optimum cut-off grade in the open-pit mines.
One of the important aspects of open-pit mine design is determination of cutoff grade, by definition cutoff grade is the grade at which the mineral reserve ca no longer be mined and processed at profit. A cutoff grade is used to assign the destination of material exploited from the mine. This destinations are: (1) to mill, (2) to the waste dump and (3) to the stockpiles. In this paper, determining the optimal cutoff grade of ore to maximize the NPV due to mining limitations, concentration and refining is described by using ICA algorithm.
Methodology and Approaches :The ICA algorithm starts with an initial population. Each population in ICA is called country. Countries are divided in two groups: imperialists and colonies. In this algorithm the more powerful imperialist, have the more colonies. When the competition starts, imperialists attempt to achieve more colonies and the colonies start to move toward their imperialists. So during the competition the powerful imperialists will be improved and the weak ones will be collapsed. At the end just one imperialist will remain. In this stage the position of imperialist and its colonies will be the same. In this paper the cutoff grade of hypothetical deposit is calculated using ICA algorithm. This algorithm has 40 country, 6 imperialist and 34 colony. Finally the results is validated by dichotomous method.
Results and One of the important parameters of open-pit mine design is determination of cutoff grade. In this paper imperialist competitive algorithm is used to optimize the cutoff grade. Since the roulette wheel mechanism is not used In the ICA algorithm and only a probability density function (PDF) is needed to reach the answer, the ICA algorithm converges faster and better to the optimum point compare with other algorithms.

Production rate is one of the most effective variables in design and economic evaluation of mining projects. Several factors such as ore deposit characteristics، market economy as well as technical aspects of the project affect the production rate. Generally، there are two types of methods for selection of mine production rate: empirical and optimized based methods. Empirical rules are mainly related to the physical characteristics of ore (depth & tonnage) or economic characteristics of the project (cash flow، project life، market، etc.). These rules could present an appropriate production rate option suitable for pre-feasibility study levels. In the second method، a production rate which maximized a certain economic indicator is defined as optimum production rate. One of the well-known economic indicators is the Net Present Value (NPV). However، the NPV maximum value may lead to an excessively high production rate (a very short mine life). The higher rates of production are practically unachievable or undesirable، i. e. it imposes a great risk of failure، with less time in hand to recover from a bad start. Moreover، shorter lives also have maximum environmental disturbances and minimum local social advantages. So، an optimized production rate could be acceptable once in one hand it safeguards a project’s minimum life and on the other hand، has the NPV maximum. Similarly، for the practical concerns of the optimum production rate، it must consider: the maximum capacity of mining (ore and waste)، maximum financial facilities، and safeguarding number of working days in a year. This study tries to present a new model to determine the optimum mine production rate employing conditional NPV maximization approach considering all mentioned constrains. The selection of an optimum production rate is performed through an iterative process. At first، reserve tonnage and average grade are determined considering a preliminary cut off grade. Then، noticing this reserve، an initial production rate is considered، and then revenue، capital and operating costs are estimated for the whole project. A new cut-off grade is obtained based on these costs and revenues and a corresponding reserve tonnage is estimated. Considering the NPV value، this iterative process must be repeated until the most suitable production rate is achieved. Applying this iterative process، a set of the possible production rates is computed. For each production rate، the related NPV is computed and consequently، the production rate corresponding to the NPV maximum value is determined. As mentioned before، this production rate is practically unachievable. Using the proposed approach the optimized production rate can be selected conditionally whilst considering all the constraints. The proposed model has been tested applying a hypothetical porphyry copper mine، and its optimum production rate has been computed.