Visual and simulation modeling of coal mining processes taking into account mining and geological conditions

Abstract

The efficiency of the coal mining mechanized complexes depends on timely predicted correction of technological parameters and technical conditions, an adequate change in the geomechanical situation at the mining site. We propose to ensure the completeness, timeliness of informational reflection of processes, the possibility of their analysis and forecasting, through the use of modern information technologies. Therefore, the development of computer-integrated decision-making systems for adoption of managerial decisions and scenarios for simulation is, by no means, an important area of research. Using WebSphere Business Modeler, business process templates were developed for "Coal mining", a process simulation, scenarios simulation and a dynamic analysis of simulation results were obtained.
The proposed business process template "Coal mining" is practical and can be used by the chief engineer to predict the daily burden of cleansing. It is possible to take into account expert knowledge before launching each simulation, altering the probability of Mining geological conditions, which correspond to satisfactory and unsatisfactory geological conditions, and «Degree of incisors», which are responsible for the incisors of the combine harvester. It is also possible to set the number of cycles that can pass the coal harvester per day, which will be created in the process of performing simulation
The use of developed simulation models for the coal mining process allows us to: make objective evaluation of the daily load (productivity) of the coal-face, depending on the actual state of the equipment of the mechanized complex; correct the quantity of spare parts of coal-mining equipment and carry out its repair, which can significantly reduce unplanned downtime and consequently increase the mining productivity; reduction of decision-makers number as well as the clear distribution of responsibilities between them, reduces the number of errors and improves the manageability of the mining enterprise.
The proposed automated system for an effective managerial decision-making, unlike those known in the literature, is based on modern unique expert data of a particular mining enterprise.