Applying IT Systems to Diagnose the Operation of Mining Machinery - Jarosław BRODNY (Communications of International Proceedings, 2021)
The process of underground mining is one of the most complex production processes. This is primarily due to the environment in which it takes place, namely high uncertainty and variability of physical and chemical conditions. The reason for this state is the disturbance of the balance in the rock mass, which results in various types of unforeseen states and events. This, in turn, makes working in such conditions both immensely dangerous and difficult. Therefore, both mechanization and automation are of great importance for this process to be efficient. Equipment that is used in the process of underground mining, including all types of machinery, is to replace human labor, and thus must be characterized by very good operational and reliability parameters. Their high durability, efficiency and failure-free operation are necessary conditions for achieving the assumed production goals. Increasing requirements as to the efficiency of the mining production process and information and communication technology (ICT) changes observed in the global industry have resulted in the increasing use of information technology systems in mining machines. The machines used nowadays are very complex mechatronic systems that enable their precise operation and obtaining a lot of data on their operational parameters. These data, after appropriate processing and analysis, are a valuable source of information regarding the assessment and analysis of their work. On this basis, it is also possible to carry out their diagnosis to obtain an assessment of the technical condition of machines, their operational parameters and, for example, production quality. This paper presents an example of applying IT systems to diagnose operational parameters of longwall system machines used in the mining process. The presented methodology and the developed tool in the form of an IT platform as well as the results are a response to the growing demand for information on the condition of machinery during the implementation of production processes in the mining industry.
Keywords: Mining Machinery; Technical Diagnostics; Production Efficiency; Mining Operations; Industrial Automation Systems