برنامه ریزی تولید

Short term mine scheduling aims to provide a constant amount of material to the milling facility. Among the available approaches, mathematical modeling is reliable in determining an optimum solution. Cut and fill mining is conducted in mineral reserves with weak surroundings. In this paper, a new mathematical model is introduced to production scheduling of drift and fill mining method while the special constraints of cut and fill mining is considered. The model is capable to consider mining operation in several levels. The model is applied for stope sequencing in Anguran mining project. The data from the +2721, +2733 and +2737 levels are used for production scheduling and stope sequencing. The Anguran underground project is a cut and fill mining project. In this mine the levels are separated into 2 northern and southern panels. The results show that simultaneous mining of +2721 and +2737 levels is capable of reaching the predetermined production level with a maximum deviation of 2.4%.

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.

Production planning defines the drawpoint extraction percentage in order to a deterministic destination (processing factory) according to scheduling objectives. One of the main problems in such planning is related to the lack of integration designing factors. So, there is a need to develop a model for mine scheduling using all factors influencing the strategic plan. In the current study, the Mixed Integer Linear Programming (MILP) has been developed according to metallurgical constraints. The maximum and minimum cut of grade as well as relative grade constraints are used to produce a real production from drawpoints according to the dilution control. The CPLEX software is used as a MILP solving framework, and also MATLAB to develop mathematical models. The application of the models based on metallurgical constraints was validated using 85 drawpoints over 12 periods. The results showed that in usual condition, the reduction of NPV was only 9% with the proportional non-distribution of average grade 24% of the maximum grade in the drawpoints, while by applying the metallurgical constraint this was reduced to 4%. Finally applying the metallurgical constraints with other operational constraints presented the real production planning.

Production scheduling is the most important and influential issue in open pit and underground mining design and planning. The main purpose of mine production planning is time scheduling and determination of mine activities sequencing under some technical and extraction constraints in order to achieve one of the following goals: maximizing Net Present Value (NPV), the amount of ore extraction or mine life. Underground mine planning optimization which is used to determine the sequence of stopes extraction, is difficult due to the complexity of decision making and the interaction between existing constraints. Since, mathematical programming techniques are capable for solving complex and multi-limiting problems, they can be used for optimization purposes. In this study, after reviewing previous studies on the design and planning of underground mine production, the step by step explanation of a proposed model based on Integer Programming (IP) has been addressed. In order to validate proposed model, an example of 9 stopes was considered. First, the sequence of extraction was carried out using manual design and then using extended mathematical model in GAMS/CPLEX software. The current NPV obtained by manual production scheduling was 8.211 million dollars. While, this value for mathematical model was 8.331 million dollars. In other words, NPV value in mathematical model was 1.46% higher than manual method which indicate the power of mathematical programming for solving complex problems.

The block extraction sequence is among the most challenging and important issues that should be regarded through whole mining operations to reach the maximum profit amount. Such Open-pit Production Scheduling problems can be solved under either deterministic or non-deterministic states. This study aims to model the problem applying robust counterpart linear optimization which uses the box set based counterpart. Block economic value, as the objective function coefficient and operational capacity, as the constraints coefficients, are considered as uncertainty sources. Exact mathematical modeling using CPLEX solver, is applied to solve the box counterpart. The model, which was solved in deterministic and uncertain conditions, terminated in results with some differences in scheduled plans.

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.

Mining is regarded as one of the most polluting sources of environment due to the production of toxic acid wastewater. Considering the environmental impacts of mining in the stage of mine production planning development can potentially reduce the harmful effects of this industry on the environment. In this research, attentions have been paid to the planning of production in Sungun Copper mine looking at parameters and environmental impacts. For this propose, field studies were conducted and chemical analysis, as well as exploratory and mapping data for planning of environmental production have been carried out, and various sections of ore have been evaluated with a view of the production of waste water. After modeling the mineral deposit and providing a block model, toxic elements content was determined for each block using the Kriging method, and the weight and effect of the blocks were determined using the entropy method. The block model in contrast to conventional production planning methods that include only grade of minerals, considers the wastewater production capacity of each block and its degree of pollution. Finally, by designing a production planning based on the environmental impacts of the toxic elements prevailing in Sungun copper mine eight operational phases were designed for this deposit. In this planning, blocks in the first pitt with a mean pollution level of 1141 and those in the final pit with an average of 52 have been found to represent the highest and lowest potential, respectively, producing harmful wastewater into the environment.