This work deals with a model development to predict the availability of continuous systems at the open pits using the artificial neural networks. The main idea of this work is to improve the analytical approach with initial assumption that the time length distributions of a faulty system have an exponential distribution. Data related to the I ECC(excavator, conveyors, crushing plant) system of the Open Pit Drmno Kostolac are used for this work. The aim of this work is to improve a model for predicting the availability of continuous systems at the open pits. On the basis of [ ], [ ], and [ ] values, presented in this work, it is concluded that the model, obtained by the use of neural network, has a higher predictive power compared to the analytical approach. A corresponding simulation is created on the basis of obtained model that should a scope of the system availability for each type of failure. Also, a more precise image of the availability of continuous systems at the open pits is given on the basis of simulation.

This work presents a model for determining the availability of continuous systems at open pits by applying fuzzy logic and fuzzy inference systems. The applied model was formed by the synthesis of independent partial indicators of availability. The model is based on an expert system for assessing the availability of continuous mining systems. The availability of the system, as a complex state parameter, is decomposed into the partial indicators, reliability, and convenience of maintenance, and the fuzzy compositions, used for integration the partial indicators, are the max–min and min–max compositions. The advantage of this model in comparison to the conventional models is that it takes into account the effect of practical indicators of availability, does not require long-term monitoring, and records necessary to determine the time picture of the system state. This model for determining the availability has a role to help responsible persons at open pits in the planning and control of exploitation, and the adoption of an appropriate maintenance strategy, all with the aim of stable production and cost reduction. The presented model can be used as a tool for the quick assessment of system availability, based on expert judgments and assessments.

This paper presents a model for determining fuzzy evaluations of partial indicators of the availability of continuous systems at coal open pits using a neuro-fuzzy inference system. The system itself is a combination of fuzzy logic and artificial neural networks. The system availability is divided into partial indicators. By combining the fuzzy logic and artificial neural networks, a model is obtained that has the ability to learn and uses expert judgment for that learning. This paper deals with the ECC system (bucket wheel excavator-conveyor-crushing plant) of the open pit Drmno-Kostolac, which operates within the Electric Power Company of Serbia. The advantage of a model of this type is that it does not rely on the historical experiences of experts and usual predicted values for the fuzzy evaluation of partial indicators, which are based on the assumption that similar systems affect availability in a similar way. The fuzzy evaluation of partial indicators is based on historical data for the specific system for which the model was created. As such, it can more accurately predict continuous systems availability on the basis of expert evaluations in the appropriate time period. Another advantage of this model is that the availability is estimated on a quarterly basis, which gives a more accurate view because it uses a smaller time period with more similar characteristics and, thus, includes certain external influences which are related to the quarterly meteorological conditions.

This work presents a method of determining the dynamics of development the open pit Gacko in the zone roof coal series with the annual capacity 3∙106 t/year of run-of-mine coal using the module cut evaluation of the software package Gemcom Gems. Defining the dynamics was preceded by optimization of the open pit that is done in the software Whittle. By optimization, the optimum boundary of mining (final contour) was obtained which includes 66∙106 t of run-of-mine coal. The contour of the open, obtained in the process of optimization, was used as the final contour of dynamics of the open pit development. Dynamics was developed for the period from 2016 to 2036 (until the end of service life). In the first 5 years, a detailed dynamics was made for the annual period, and after the fifth year, the dynamics was made for a five-year period.

This paper presents a model for determining the availability of continuous systems at open pits using the neuro-fuzzy system. The concept of availability is divided into partial indicators (synthetic indicators and sub-indicators). The presented model in relation to already existing models for determining availability uses a combination of the advantages of artificial neural networks and fuzzy logic. The case study addressed the I ECC (bucket wheel excavator–conveyors–crushing plant) system of the open pit Drmno, Kostolac. In this paper, in addition to the ANFIS model for determining the availability of continuous systems, a simulation model was developed. The obtained results of the ANFIS model were verified with the help of a simulation model that uses certain assumptions about the distribution of failures. This paper was created as a result of several years of field and theoretical research into the availability of continuous systems in open pits, and completes a cycle that consists of several published articles on the subject of modeling the behavior of these systems in real time using a time picture of the state, expert assessment, simulation and AI models, while respecting the multidisciplinarity of the problem (mining technological, mechanical, and information technological aspects). The developed ANFIS model is a key instrument for improving operational efficiency and resource management in the mining sector. Its ability to accurately predict the availability of the ECC system brings not only operational benefits through reduced downtime and optimized maintenance, but also a potential reduction in overall costs at coal open pits. Such an innovative model marks a significant step forward in the mining industry, especially when it comes to continuous systems in coal open pits.

Protection of the open pit against water is very important, especially if the open pit is located in the complex conditions regarding protection of the open pit against water. To reduce the investments, it is proposed to define the protection system of the open pit against water for a longer period. In the specific case, the technological system of protection against water was considered at the open pit Gacko with construction the canal system with a The Cumulative water collector. The aim of developing such system is the water directing water the river Musnica riverbed and effective protection of the open pit.