Multi-Criteria System's Design Methodology for Selecting Open Pits Dump Trucks

1. Introduction

The largest volume of transportation of rock mass in open-pits is carried out all over the world by dump-trucks of various carrying capacities [1,2]. The cost of transporting rock mass increases by 20-30% on average for every 100 m of depth in deep pits. The share of these costs reaches 70% or more of field development total cost [3,4,5]. At the same time, the maximum transportation distance is 10 km for deep open pits.

Cost reduction is achieved by combining modes of transport. The combination of automobile and conveyor transport or cyclical-and-continuous method is the most common in open pits [6,7]. Most researchers consider this method promising for deep open pits [8,9]. The implementation of this method requires the creation of transshipment points. The effectiveness of schemes with combined transport depends on the depth of the transshipment points in the open pit. Nevertheless, the share of transportation by dump trucks remains considerable in this case [10,11].

Many alternative options for the layout of the open pit transport system have appeared in mining enterprises currently. This is due both to an increase in the carrying capacity of new models of mining dump trucks, and the number of dump truck manufacturers. The tendency to increase the carrying capacity of dump trucks to ensure the required cargo turnover is especially relevant for large and deep open pits [12,13]. The maximum carrying capacity of modern mining dump trucks has reached 450 tones [3]. According to [14], nine major manufacturers of mining dump trucks are represented on the world market. However, their number tends to increase. In addition, the range of mining equipment is constantly expanding.

These factors are the reason for a significant variety of applied technical and technological solutions. The results of 13 open pit projects carried out by the authors show that the most common differences are the following: the load capacity of dump truck models in the same open pit – 5 times; the estimated width of the transport berm – 1.5-3 times; the depth, and angles of the conveyor in different open pits – 2–4 times; the number of dump trucks for various transport complex layout options, but for the same open pits depth and productivity – up to 10 times [10] (Figure 1).

Table 3. dump trucks account for one mining excavator at a depth of open pits up to 200 meters, and at a depth of 200–600 meters – 10 or more dump trucks. Moreover, open pit transport constitutes the bulk of the equipment and is 2.1-3.7 times higher than the number of all other types of equipment for the main technological processes (Figure 2).

The negative impact of the mining enterprise on the environment forces as the number of equipment increases. Especially relevant are the issues of the negative impact of equipment operation on the atmosphere in deep open pits. The main negative impact from open pit equipment is emissions from the operation of dump truck engines and dust during the transportation of rocks [15]. Dump trucks account for 60 to 75% of emissions (Figure 3). The presented results of these author's studies do not consider the volume of emissions during the production of blasting. These emissions are not permanent and do not affect the work of personnel and equipment in the open pit, since until the complete dispersion of the dust-gas cloud, after blasting, the resumption of work in the open pit is not allowed.

In this regard, environmental issues acquire a significant influence on the design decisions for deep open pits [16,17,18,19].

Improving the efficiency of deep open pits operations requires the consideration of many alternative solutions in such conditions. One of the most important decisions is the selection of a specific dump truck model. The presence of numerous factors and options makes the selection issue complex and multi-criteria.

The main goal of this study is to develop a methodology for the multi-criteria selection of a dump truck model.

The rest of the paper is organized as follows. A literature review of studies on the factors, methods, and criteria for selecting a dump truck model is presented in Section 2. The original system of criteria for selecting a dump truck model and the selection methodology using the multi-criteria FUCOM method is presented in Section 3. Section 4 contains a case study on the proposed methodology effectiveness. Finally, conclusions and recommendations for the application of the selection methodology and future research are presented in the Conclusion.

2. Literature review

2.1. Factors for Selecting a Dump Truck Model

One of the main factors is the excavator model, the choice of which, in turn, depends on the height of the ledge, the physical and mechanical properties of the rocks and the required productivity of the open pit [20]. However, numerous variants of dump truck models are possible for the same excavator model.

The authors [21] propose to consider the properties of rocks, the distance of transportation, the amount of work and the rate of the deposit development when selecting a dump truck model. The authors of the study [22] consider the ratio of the dump truck body capacity to the capacity of the excavator bucket, which should be in the range from 4-6 to 7-8, to be the most important factor. In addition, they suggest selecting higher capacity models as the open pit deepens, transport distances increase, and rock mass transport volumes increase. Three factors are proposed to be considered in the paper [23]. The first factor is the maneuverability of the dump truck, which depends on its technical characteristics, including the load capacity and size of the dump truck. The second factor is the carrying capacity, which must correspond to the transportation volumes. Finally, the third factor is safe working conditions.

Many studies are devoted to the choice of a rational model of a dump truck based on economic factors. The competitiveness coefficient, which considers the prices of compared models, as well as several technical characteristics, was proposed in [24]. The indicator of the efficiency of transport work is studied in [25]. This indicator considers changes in mining conditions and the economic situation. The value of the total discounted costs for the acquisition and operation of dump trucks [3] is one of the common indicators for evaluating dump truck models. Economic losses from downtime of dump trucks [26], including because of their breakdowns [27], are considered when choosing dump trucks. Options for using fuel [28] and other energy sources [15,29] are determining the amount of operating expenses for various models of dump trucks. Researchers in [30,31,32] suggest considering the possibility of using conveyors in an open pit when selecting dump truck models. The choice is also made based on an economic comparison of the options in these studies.

The cost of buying dump trucks and subsequent operating expenses are major factors in business practice. To perform the corresponding calculations, various software tools are used, for example, PTV Vissim [33] in the method [34].

However, the emphasis mainly on economic indicators does not allow considering the environmental friendliness and safety of operation of dump trucks. Progressive mining enterprises are beginning to shape their mission in accordance with the concept of sustainable development. Social and environmental factors, as well as factors of automation of transportation and production processes, begin to influence decision-making [35,36,37] at such enterprises.

The systematic consideration of these factors is especially difficult when selecting a model of dump trucks for deep open pit conditions. This is because the fleet of dump trucks is completely replaced as the open pit deepens.

Thus, technical, technological, economic, environmental, geological, and organizational factors must be considered when selecting dump truck models to ensure the efficient operation of deep open pits.

2.2. Multi-Criteria Decision-Making Methods

Numerous influencing factors, as well as the specifics of work at great depths, predetermines the need for a multifactorial and multicriteria approach to solving the problem of selecting mining dump trucks. Therefore, we propose to use multi-criteria methods to select a dump truck model. These methods are based on expert ranking of criteria for evaluating alternatives, followed by ranking of alternatives in accordance with the rank of criteria. This approach allows considering many conflicting factors and requirements. Currently, such methods are widely used in mining and in the choice of transport and handling systems for open pit mining. We performed an analysis of the experience of using MCDM to identify the most used methods. The result of the analysis is presented in Table 1.

The Analytic Hierarchy Process (AHP) or fuzzy AHP method, as well as its combinations with other methods (TOPSIS, PROMETHEE, ELECTRE) is used most often for the selection of dump trucks and loading and unloading systems in open pits. The analyzed methods (Table 1) are widely used in various research areas, use both quantitative and qualitative evaluation criteria, are relatively simple, and are also implemented in convenient software.

The main disadvantage of the considered methods is many pairwise comparisons of criteria. This makes the procedure of multi-criteria evaluation time-consuming with numerous criteria. Several researchers in the field of MCDM have proposed more efficient methods for multi-criteria evaluation of [51,52,53]. Full Consistency Method (FUCOM) [54] is the most promising according to the authors. However, we were unable to find studies on the application of this method in mining. Given the large number of factors influencing the choice of dump trucks for open pits, we suggest using FUCOM.

3. Models and Methods

3.1. Methodology of Forming a System of Criteria for Selecting a Dump Truck Model

We have developed a methodology, the result of which was the original universal system of criteria for selecting a model of mining dump trucks. The methodology consists of the following 5 stages.

Stage I. Analysis of research in the field of selecting mining equipment, dump trucks, optimizing the operation of mining vehicles. Identification of factors and formation of a list of selection criteria.

Stage II. Primary grouping of criteria according to factors influencing the selection of a dump trucks. Grouping is done by establishing relationships between factors and criteria.

Stage III. Formation of an initial data set. We suggest the following list of data: the range of values, the unit of measure, the target value of the criterion. In addition, the description of the criterion should contain its name, a brief explanation, the name of the corresponding group of criteria, and an indication of the source of data on the range of quantitative values of the criterion. An example of the initial data collection form is presented in Table 2.

Stage IV. Secondary grouping of criteria. This grouping is recommended to equalize the number of criteria in the groups. Such adjustment is necessary for the correct ranking of criteria by the FUCOM method. Secondary grouping is carried out by combining similar criteria in terms of meaning, units of measurement, range of acceptable values and target values. In addition, it is allowed to combine groups of criteria according to the similarity of the relevant factors. In addition, we recommend excluding conditionally constant parameters, as well as dependent parameters, from consideration. For example, the technical indicator “duration of unloading a dump truck” is excluded, since it is conditionally the same for all mining dump trucks and the time spent on unloading does not exceed 1% of the total duration of the trip. Another technical indicator, “average rolling resistance,” is also excluded, since its value depends on other criteria already included in the group of technical criteria.

Thus, we received four groups of criteria: technical, technological, environmental, economic and organizational. In addition, we recommend excluding conditionally constant parameters, as well as dependent parameters, from consideration. For example, the technical parameter “duration of unloading a dump truck” is excluded, since it is conditionally the same for all mining dump trucks and the time spent on unloading does not exceed 1% of the total duration of the trip. Another technical parameter, “average rolling resistance,” is also excluded, since its value depends on other parameters already included in the group of technical criteria.

Thus, we received four groups of criteria: technical, technological, environmental, economic and organizational.

Stage V. Distribution of criteria by expert competence levels for further ranking of criteria by the FUCOM method. Such a distribution is necessary to obtain the most objective and qualitative assessment of the criteria. We proceeded from the assumption that the most qualitative assessment of the criteria can be given by experts with competencies that best match the content of the criterion. We propose to allocate three levels of expert competence, namely, strategic, design, and optimization.

Level 1 – Strategic. Experts of this level have competencies in the field of strategic management of a mining enterprise. These experts evaluate the criteria that determine the company's financial performance and reputation. We classified owners or presidents of companies, key executives, general, commercial, and technical directors, as well as their deputies, as first-level experts.

Level 2 – Design. The second level experts evaluate the criteria that are used in making design decisions. The experts at this level are the heads and specialists of the design and engineering department, chief engineers, miners, geologists, mine surveyors, heads and specialists of planning and economic departments, heads of labor protection and environmental departments.

Level 3 – Optimization. At the third level, experts evaluate the criteria directly related to the process of operation and maintenance of dump trucks in an open pit. Such experts include mechanics, power engineers, heads of open pits, transport departments and shift supervisors.

A flowchart of the proposed methodology for systematizing the selection criteria for dump trucks is shown in Figure 4.

The presented methodology is general for solving the criteria system design problem. The initial data are scientific publications and the results of surveys of industrial experts. Nevertheless, the authors propose to use the developed system of criteria (see Section 4) as a base one, since it is the result of an analysis of all currently known factors considered when choosing models of dump trucks.

3.2. FUCOM Method for Calculating Criterion Weights

The Full Consistency Method (FUCOM) [43] was chosen to calculate the weight of the criteria that determine the selection of dump trucks. The choice of the FUCOM method is justified by the fact that in comparison with AHP, ANP and BWM, it provides the following advantages [54,55,56]:

- Minimum number of pairwise comparisons of criteria equal to (n -1), compared to AHP (n(n - 1)/2), and to BWM (2n - 3).

- Simple algorithm is used for prioritization of criteria by decision makers.

- High reliability of the result.

- Allows obtaining optimal weighting factors with the possibility of validating them, showing the consistency of the results.

Thus, the FUCOM method, unlike AHP and BWM, provides an opportunity to perform model checking by calculating the error size for the obtained criterion weight vectors, to determine the degree of consistency and thus adequately reflect errors in expert judgments.

The FUCOM method has been used in transportation to evaluate and select: alternative fuel vehicles [57], human resources of a transportation company [58] and others. In the mining industry — to assess the mineral potential of new deposits [56].

The basic steps of the FUCOM method are:

Step 1. Ranking of criteria C = {C₁, C₂, …, C_j, …, C_n} according to their significance, starting from the criterion that will have the highest weight to the criterion of the lowest significance. Each j-th criterion is assigned a rank k

$${C_j}_{\left(1\right)}>{C_j}_{\left(2\right)}>...>{C_n}_{\left(k\right)}$$

(1)

Step 2. Comparison of ranked criteria and determination of comparative priority Φ for criteria

$${\phi }_{k/(k+1),}k=\mathrm{1,2}\dots ,n,$$

(2)

$$\Phi =\left({\phi }_{1/2},{\phi }_{2/3},...,{\phi }_{k/(k+1)}\right).$$

(3)

Step 3. Calculation of the final values of the weight coefficients of the evaluation criteria forming the transposed matrix ω = (ω₁, ω₂,…, ω_j, …, ω_n)^T. The values of the matrix ω must satisfy the following two conditions.

The ratio of weighting coefficients should be equal to the comparative priority of criteria φ_k/(k+1) determined at the second step

$$\frac{{\omega }_k}{{\omega }_{k+1}}={\phi }_{k/(k+1)}.$$

(4)

- The final values of weight coefficients should satisfy the condition of mathematical transitivity

$${\phi }_{k/(k+1)}\otimes {\phi }_{(k+1)/(k+2)}={\phi }_{k/(k+2)}$$

(5)

Considering (4) and (5) we obtain

$$\frac{{\omega }_k}{{\omega }_{k+1}}\otimes \frac{{\omega }_{k+1}}{{\omega }_{k+2}}=\frac{{\omega }_k}{{\omega }_{k+2}}.$$

(6)

Thus, we obtain a new condition, which must be satisfied by the final values of the weight coefficients of the evaluation criteria

$$\frac{{\omega }_k}{{\omega }_{k+2}}={\phi }_{k/(k+1)}\otimes {\phi }_{(k+1)/(k+2)}$$

(7)

Step 4. Solution of the model for calculating the values of weighting coefficients of evaluation criteria. The model minimizes the value of deviation $\chi$ from the full consistency of the results

$$\mathit{min}\chi ,$$

(8)

$$\chi =\left|\frac{{\omega }_{j\left(k\right)}}{{\omega }_{j(k+1)}}-{\phi }_{k/(k+1)}\right|,\forall j,$$

(9)

$$\chi =\left|\frac{{\omega }_{j\left(k\right)}}{{\omega }_{j(k+2)}}-{\phi }_{k/(k+1)}\otimes {\phi }_{(k+1)/(k+2)}\right|,\forall j,$$

(10)

$$\sum _{j=1}^n{\omega }_j=1,\forall j,$$

(11)

$${\omega }_j\ge 0,\forall j.$$

(12)

As a result of solving the model (8-12), the values of evaluation criteria are obtained ω = (ω₁, ω₂,…, ω_j, …, ω_n)^T.

The proposed methodology for determining the weights of criterion groups and criteria for selecting dump trucks using the FUCOM method is presented in Figure 6.

Figure 5. Methodology for ranking criteria for selection of dump trucks.

Figure 5. Methodology for ranking criteria for selection of dump trucks.

4. Results

4.1. Data Collection and Formation of a Universal System of Dump Truck Selection Criteria

The selection of a dump truck model using multi-criteria methods requires the definition of a criterion set for evaluating various models. We analyzed 49 studies to identify the criteria used to address this issue. We analyzed studies on the selection of a dump trucks, equipment complexes for open pits, as well as studies on the features of transport operation in deep open pits. The results of the analysis are presented in Table 3.

Six groups of criteria (Stage 2) were initially identified: technical, technological, geological, economic, environmental, and organizational. The number of criteria in the initial groups turned out to be uneven, from 4 to 26.

The authors identified the following features of the use of dump truck selection criteria in the analyzed studies:

• Variety of criteria. 68 different criteria identified.
• Significant variation in the number of criteria used by different authors. The minimum number of criteria is 2, the maximum is 26.
• Differences in the understanding of the criteria by different authors.
• The predominance of criteria that we previously attributed to the group of economic criteria. 58% of the authors consider only capital and operating expenses.
• 25% of the total number of criteria are unique, that is, they are mentioned in only one study.
• 51% of the total number of criteria used in no more than three studies. We characterized such criteria as rarely used.
• 19% of the total number of criteria is used most frequently, that is, in ten or more studies.
• Some researchers use the criteria to select not only dump trucks, but also with other equipment, for example, when justifying excavator-and-dump truck complex options.
• A different number of levels of the criteria hierarchy – from 1 to 2. In the latter case, the level of criteria and subcriteria is distinguished.
• A variety of ways and systems for grouping criteria are used.
• 57% of the criteria are quantitative, for the remaining criteria qualitative assessments are used.
• We have not identified studies that systematically use the entire set of known criteria for selecting dump trucks.

Figure 6. Distribution of the number of criteria in predefined groups.

Figure 6. Distribution of the number of criteria in predefined groups.

The variety and large number of criteria for choosing dump trucks motivates us to develop a universal system of criteria.

The sources of data on the criteria, as well as the units of measurement, ranges of values and target values of each criterion are defined in Stage 3 of the methodology.

Secondary grouping of criteria was carried out in accordance with the recommendations of Stage 4 of the methodology. This resulted in 4 groups of criteria. This allowed to eliminate the imbalance of the number of criteria in separate groups, which made further calculations difficult, as well as to reduce the number of criteria under consideration by 36% — from 68 to 43 criteria.

Finally, the criteria were regrouped by competence levels and areas of responsibility of different mining specialists (Stage 5). We assigned 13 criteria to the Strategic level, 18 criteria to the Constructive level, and 15 criteria to the Optimization level. Some criteria were assigned to the areas of responsibility of specialists of several levels.

The system of dump truck selection criteria was formed because of the developed methodology (Table 4). The authors propose to use the developed system of criteria as a universal one because it includes all currently known factors influencing decision-making on the choice of dump truck model.

The panel of experts to determine the weighting of the criteria consisted of managers and specialists from various mining companies. Such enterprises were open pit mining iron ore, copper ore, gold ore, construction rocks, as well as raw materials for chemical and metallurgical industries. The composition of the expert group is presented in Table 5.

Experts completed questionnaires, the form of which differed for different levels of expert competence. The questionnaires consisted of the following sections: selection of the expert's competence level (Appendix A), instruction (Appendix B), questionnaire to assess the importance of criteria groups (Appendix C). The questionnaires for assessing specific criteria by experts of different levels have a form like Table C1. The difference lies in the set of specific criteria evaluated (Table 6, Table 7 and Table 8). The names of the group of criteria are present in all questionnaires, while the composition of criteria in the questionnaire depends on the expert's level of competence (Table 4). The combinations of parameters and indicators depending on the level of competence are presented in Table 6, Table 7 and Table 8.

4.2. Results of Expert Evaluation of Criteria Groups and Criteria for Selection of Dump Trucks

The results of evaluation of criteria groups for selection of dump trucks by experts of different levels of competence are presented in Table 9, Table 10 and Table 11.

The results of expert evaluation of the selection criteria for dump trucks are presented in Table 12, Table 13 and Table 14.

4.3. Results of Ranking the Criteria Groups and Criteria of the FUCOM Method

The results of calculating the weights of the groups of criteria for selecting dump trucks in accordance with the FUCOM methodology (Section 2.2) are presented in Table 15 and Figure 7. The value of deviation $\chi$ for all criteria groups and for all experts is equal to 0.

The analysis of results of assessment of criterion groups weights confirmed the hypothesis about differences of these assessments by experts of different competence levels.

Level 1 experts gave the highest priority to the group of Technological criteria (C2) — the weight coefficient of this group is 0.4416. The Technical (C1) and Economic-Organizational (C4) groups of criteria have almost the same weight — respectively 0.211 and 0.2548. The lowest priority is given to the group of Environmental criteria (C3), with a weight coefficient of 0.0926.

Level 2 and 3 experts give the highest priority to the group of Technical (C1) criteria, the weight coefficients for which are 0.4202 and 0.4320, respectively. This is followed by Technological (C2) – 0.2842 and 0.3263 and Economic-Organizational (C4) – 0.1499 and 0.1229. These experts also put the Environmental (C3) group in last place – 0.1457 and 0.1188.

The group of Environmental (C3) criteria received the least weight according to the assessments of experts of all levels.

This result indicates the insufficient state regulation of environmental problems at the studied mining enterprises. On the other hand, modern research proves the necessity to revise priorities in decision-making for mining enterprises towards environmental aspects [16]. For example, studies [35,36,37] show the effectiveness of excluding economic criteria at the stage of preliminary assessment of criteria, since economic criteria in most cases are evaluated by experts according to the highest priority.

The results of calculating the weights of the selection criteria for dump trucks are presented in Table 16, Table 17 and Table 18. The value of deviation $\chi$ for all groups of criteria and for all experts, as well as in the case of groups of criteria, is equal to 0.

The results of the evaluation of the weighting of the selection criteria for dump trucks, performed by the FUCOM method, are presented in Table 19, Table 20 and Table 21 presented. The results of criteria ranking (Global weight) by expert competence levels are presented in Figure 8, Figure 9 and Figure 10. The criterion groups and the criteria that received the highest weight values are in bold.

Estimates of dump truck selection criteria significance differ according to experts of different levels of expertise. The same situation is observed here as in the case of criteria groups.

The authors made several assumptions at the initial stage of the study. These assumptions related to the orientation of experts of a certain level of competence to the criteria corresponding to their field of activity. The hypothesis that Level 1 experts prioritize economic and environmental criteria was if that these experts are oriented towards strategic decisions. Such decisions include, for example, maximizing the financial results of the whole company, as well as strengthening the company's reputation by implementing various environmental and social measures. Emphasis on technological criteria was expected in the Level 2 experts, as these experts are responsible for operational planning. Finally, prioritization of technical criteria was expected in the assessments of Level 3 experts, as they directly operate dump trucks and are interested in their reliability and safety. However, all the above hypotheses were not confirmed. A detailed analysis of the results obtained allowed us to find explanations for the differences between the actual results and the expected ones.

The assessments of criteria groups and local criteria did not coincide among experts of all competence levels. Discussion of the obtained results with experts allowed to establish the reason for such differences. It was found that experts perceive groups of criteria as target criteria and local criteria as constraints to be observed in the process of achieving target criteria.

For example, Level 1 experts prioritized the group of Technological criteria (C2) as target criteria, but the technical criterion “Useful life of dump trucks” (C1.1) was selected by them as a priority local criterion. Level 2 experts chose the group of Technical criteria (C1) as the target criteria, as they are oriented in their activities towards the most efficient operation of machinery. However, the same experts prioritized the local criterion “Type and geometry of deposit” (C3.4) from the Environmental criteria group. This is because the operational decisions of these experts are determined by the actual configuration of the ore body, which may differ significantly from the design configuration. Operational adjustments complicate current and operational planning and are therefore perceived as constraints by this group of experts. Although the Level 3 experts expectedly prioritized their target group of technical criteria (C1), they selected “Climatic zone match” (C3.5) from the Environmental criteria group as the priority local criterion. The main reason for this discrepancy was explained by the fact that the mining enterprises where the interviewed experts work are located in the harsh climatic conditions of the Russian Federation and the Republic of Kazakhstan. Therefore, the influence of climatic conditions, in particular, sharp fluctuations in ambient air temperature is perceived by experts of this level as factors complicating the operation of the mining enterprise, reducing the reliability and safety of dump trucks.

The values of global criteria weights for each group of experts is the result of striving for a balance between target and local criteria — constraints. For example, the technological criterion “Production rate” (C2.5) received the maximum weight from the Level 1 experts because the achievement of the target values of this criterion is the main indicator of the efficiency of experts from this group. We make a similar explanation for the results of other groups of experts. The criterion “Payload capacity” (C1.9) received the maximum global weight in the group of Level 2 experts, and the criterion “Required dump trucks fleet” (C2.7) — in the experts of Level 3.

The findings also explain the non-confirmation of the hypothesis about the priority of certain criteria among experts of certain levels. There are two reasons for this. The first reason is the selection of specific experts. For example, experts who are not owners of mining enterprises or top managers formed the composition of the Level 1 expert group in our case study. Therefore, they selected the technological group of criteria as the target criteria rather than the expected group of economic or environmental criteria. The second reason is the two-tiered nature of our proposed criteria system. The criteria with the highest local weight do not belong to the group of criteria also with the highest weight among experts of all levels. This also indicates differences in the evaluation of target criteria — groups and limiting criteria. We define the criteria with the maximum global weight as compromise criteria, compliance with which allows achieving the target criteria while complying with the limiting local criteria.

Figure 11 shows the results of averaging the weights of the criteria groups in comparison with the assessments of experts of different levels. The average values almost completely coincide with the results of Level 3 experts' assessments. However, Level 1 and Level 2 experts evaluated the groups of technical and technological criteria differently. Level 1 experts gave priority to the group of Technological criteria (C2), while Level 2 experts most highly evaluated the significance of the criteria of the Technical criteria (C1). The obtained result is explained by the peculiarity of work organization at the studied open pits, when direct executors (Level 3) are oriented to the requirements of managers pursuing different, often opposite goals.

The analysis of the obtained results allowed us to conclude about the productivity of the proposed methodology of forming a system of criteria for selecting dump trucks. The dump truck fleet is a critical element of a complex quarry system. The main feature of the methodology is a two-level system of criteria, the weight of which is determined by experts of three different levels of competence. The two levels of the criteria system include the level of target and common criteria for all experts, as well as the level of criteria specific for different experts. The application of the proposed methodology for the conditions of a particular mining enterprise will allow not only to determine the criteria for selecting the dump truck model considering the existing conditions.

5. Conclusions

The problem of selecting a dump truck model is critical, especially for the conditions of deep quarries. This is due to the significant — up to 70% of the total costs of the open pit — costs of transport operation. These costs increase by 20-30% with deepening of the open pit for every 100 meters. In addition, technical and operational characteristics of the selected dump trucks should be coordinated with many parameters of the open pit development process. Inconsistency of these parameters and characteristics is the cause of reduction not only of economic efficiency of the mining enterprise, but also leads to increase in harmful impact on the environment, reduces safety and comfort of personnel work.

The analysis of operating open pits has shown the lack of systematics in solving the problem of selecting the dump truck model. Many important factors and conditions are not considered when deciding. Subjective factors often influence the choice. The lack of systematic in the assessment of influencing factors and conditions of quarries functioning is also present in the analyzed scientific studies. Different authors identify limited groups of factors and conditions that are significant in their opinion. In addition, the sets of such factors and conditions vary from one study to another.

We propose to solve the problem of selecting dump truck models for the conditions of deep open pits using the proposed methodology based on the system analysis of selection criteria and the use of multi-criteria decision-making methods. This approach, in our opinion, can ensure a balanced achievement of both economic, environmental, and social objectives of the functioning of mining enterprises.

A detailed description of the developed methodology is presented in the paper. We have chosen the FUCOM method as a multi-criteria decision-making method. The choice of this method is due to its effectiveness in evaluating a large number of selection criteria compared to other known methods. The presented methodology has two features. First, the system of criteria is two-level. The first level is formed by four groups of criteria: technical, technological, environmental, economic and organizational. The detailed justification for the selection of these groups is contained in the article. Specific selection criteria form the second level. We have created a complete list of all possible selection criteria. This set we have made based on analyzing scientific research, as well as interviews of managers and specialists of careers.

Secondly, we propose to divide specific selection criteria not only by groups, but also by levels of competence of decision-makers. We propose to distinguish three levels of competencies: Level 1, Strategic — the experts of this level have competencies in the field of strategic management of a mining enterprise, Level 2, Design — the experts at this level are the heads and specialists of the design and engineering department, chief engineers, miners, geologists, mine surveyors, heads and specialists of planning and economic departments, heads of labor protection and environmental departments, Level 3, Optimization — such experts include mechanics, power engineers, heads of quarries, transport departments and shift supervisors. We propose to form a set of evaluated specific criteria specific to each level of experts' competence.

We applied the designed methodology to form a system of dump truck selection criteria and to rank the importance of specific criteria. The criteria with the highest weight were: “Production rate” (according to Level 1 experts), “Payload capacity” (Level 2), “Required dump trucks fleet” (Level 3).

The presented system of criteria is, in our opinion, universal, because it is based on a systematic analysis of all currently known criteria for selecting dump trucks. We propose to use this system of criteria as an exemplary one at various mining enterprises. However, we propose to recalculate the ranks of criteria using the presented methodology when external conditions and factors change, as well as when expanding the set of private evaluation criteria.

In future studies, the authors will present a methodology for selecting a specific dump truck model using the developed criteria system. We also intend to evaluate all the dump truck models on the market using a case study of dump truck model selection for a deep open pit. Finally, we intend to investigate the dependence of the effectiveness of the management system of an open pit and a mining enterprise on the degree of consistency of opinions of experts of different levels of competence about the importance of one or another group of criteria for selecting a dump truck.