Abstract
The risk assessment determines threats that could appear during the execution of production system goals. Thus, manufacturing companies need to evaluate and react to the risk as well as it is possible. Due to the complexity and variable character of the mining system, as well as different types of parameters obtained at subsequent stages of the horizontal transport process, the risk was assessed according to various methods. Three stages were distinguished in the horizontal transport system of copper ore studied in the paper: tyre haulage of the shot copper ore to the transfer point, the so-called grate, transferring the output to belt conveyors and crushing solid rock into smaller pieces; transport on belt conveyors. Risk factors have been characterized for each stage. To assess the risk of the loading and haulage processes, an ANN model was built to predict the amount of ore extracted. A general linear neural network model was also built to confirm the results of the correlation analysis. One of the methods recommended for risk assessment in manufacturing companies is the Failure Mode and Effects Analysis (FMEA), which allows for calculating the risk and prioritizing it. The FMEA method allows identifying only these elements of the production system that are the most sensitive to the impact of risk factors. For the next stages of the horizontal transport process, the risk was assessed according to the FMEA method. The risk levels at each stage were different. Production systems are composed of many elements that create the reliability structure of this system. Unfortunately, the FMEA method does not allow for analyzing the reliability structure of the production system. Therefore, the new idea presented in this paper is a method of total risk assessment of the horizontal transport system of copper ore, which does take its reliability structure into account. The currently used methods of risk analysis and assessment do not take into consideration the reliability structure of the production system. The proposed method can be applied for risk assessment in other production systems characterized by a diversified structure.
Highlights
The mining system significantly differs from other production systems, even though it is subject to the same economic laws and to the market pressure of productivity and efficiency improvement (Bošnjak & Zrnić, 2012; Chaulya & Prasad, 2016; Pihnastyi & Khodusov, 2020; Więcek et al, 2019)
Stability of the production system means its ability to get back to equilibrium after disturbances caused by the occurrence of the risk factors cease
Because of the complex and variable nature of an extraction system, as well as different types of parameters at various process stages acquired by the mine, it was necessary to assess the risks of individual process stages using different methods
Summary
The mining system significantly differs from other production systems, even though it is subject to the same economic laws and to the market pressure of productivity and efficiency improvement (Bošnjak & Zrnić, 2012; Chaulya & Prasad, 2016; Pihnastyi & Khodusov, 2020; Więcek et al, 2019). Stability of the production system means its ability to get back to equilibrium after disturbances caused by the occurrence of the risk factors cease. With regard to the management of production systems, stability of the production system means its ability to execute the tasks for which it was built (Bubnicki, 2013; Burduk & Chlebus, 2009; Rosienkiewicz, 2012; Wirth et al, 2016). Values of the parameters required for the correct operation of the system are analyzed with regard to reaching the results assumed in the model that, in the case of production processes, is generally the production schedule (Mahmood, 2008). Production systems must operate in an environment that continuously affects the system and causes its disturbances.
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