Recent advances in information and artificial intelligence technologies, and more specifically in Fuzzy Logic and Fuzzy Inference Systems (FIS), have provided a new approach in solving many problems related to mineral industry. The aim of the current study is to examine the application of FIS in mineral resources extractive industry by performing a recent literature review (2010-2020) of related studies published in engineering and earth science oriented scientific journals. Firstly the principles of Fuzzy Logic and the operation of FIS are briefly discussed and a descriptive example of a FIS used in mining with bucket wheel excavators is given. Secondly the results from the literature review are presented and the advantages as well as the trends in future development are discussed.

In this study we present a generic probabilistic risk assessment methodology to evaluate the risk associated with flooding process of a pit. We use the bow-tie analysis to analyze the critical events (we focus on slope failures) and the systemic risk assessment methodology to estimate the risk for the population, for the environment and for the infrastructure. Furthermore, we perform a spatial analysis of the risk by discretizing the affected area into squares, by estimating the risk in each one and finally by creating the risk map. The methodology is implemented by specialized software that has been created in a Matlab environment for the deduction of such risk assessments. The developed methodology was applied in the area of the pit lake Most in Czech Republic.