Abstract

The main goal of this research was the development of an algorithm for the implementation of negative risk parameters in a synthesis model for a risk level assessment for a specific machine used in the mining industry. Fuzzy sets and fuzzy logic theory, in combination with statistical methods, were applied to analyze the time picture state of the observed machine. Fuzzy logic is presented through fuzzy proposition and a fuzzy composition module. Using these tools, the symmetric position of the fuzzy sets with regard to class was used, and the symmetric fuzzy inference approach was used in an outcome calculation. The main benefit of the proposed model is being able to use numerical and linguistic data in a risk assessment model. The proposed risk assessment model, using fuzzy logic conclusions and min–max composition, was used on a mobile crushing machine. The results indicated that the risk level of the mobile crushing machine was in the “high” category, which means that it is necessary to introduce maintenance policies based on this high risk. The proposed risk assessment model is useful for any engineering system.

Highlights

  • Sudden failures of different parts of engineering systems are everyday occurrences in the mining industry, and they often lead to negative consequences that can have an impact on machines, employees, or the working environment

  • Meticulous attention should be directed toward the factors that can cause a risky event, as well as toward the consequences and negative effects that can manifest after a failure

  • Due to the extensive results acquired using the risk assessment model, the methods and techniques used for the risk assessment of one element, subsystem, and technical system are presented in this paper

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Summary

Introduction

Sudden failures of different parts of engineering systems are everyday occurrences in the mining industry, and they often lead to negative consequences that can have an impact on machines, employees, or the working environment. Meticulous attention should be directed toward the factors that can cause a risky event, as well as toward the consequences and negative effects that can manifest after a failure. The consequences of a failure can have a negative impact on the structure of machines, employees, and the environment.

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