Applying IT Solutions to Analyze Unplanned Machine Downtime during the Mining Production Process - Jarosław BRODNY (Communications of International Proceedings, 2021)
Efficient mining production is a difficult task and depends on many factors. The main cause of problems reported during this process is the environment in which it is conducted. Possible natural hazards require appropriate organization and technical equipment. Both machines and equipment used during mining production must meet a number of requirements and be highly reliable. The complete use of their capabilities has a significant impact on the efficiency of the entire production process. Therefore, it is of great importance to reduce all kinds of unplanned break in the operation of these machines. The article presents an elaborated method of registering interruptions in the operation of mining machines and identifying their causes. The basis for the registration of these interruptions is an industrial automation system that allows for objective registration based on selected diagnostic signals. An important advantage of this system is the continuity of the process of recording diagnostic parameters and its low dependence on the human factor. In order to identify the causes of unplanned and recorded machine downtime, an IT tool in the form of a recording system was developed and applied. This tool, through a very friendly interface, allows the dispatcher to semi-automatically identify unplanned machine downtime. In this regard, the acquisition of undisclosed knowledge from workers is possible. The study results indicate great possibilities of using this system to identify the causes of unplanned machine downtime and, subsequently, to reduce it. In conjunction with the industrial automation system, this tool constitutes a system that allows for the objective monitoring of machinery work and, on this basis, introducing changes in order to improve their efficiency.
Keywords: Unplanned breaks in machine operation; machine availability; production efficiency; mining operation; databases; industrial automation