The risk assessment of engineering systems represents an important part of the quality of service and dependability. The existing methods for risk evaluation use crisp sets for rating partial indicators’ proposition and their cumulative products as an overall indicator. In this paper, existing FMEA and FMECA methods have been improved using the fuzzy expert system for calculating the risk priority number. The application of fuzzy logic allows the use of linguistic descriptions for risk analysis. In this way, the state of the system in terms of risks and consequences is better described. The settings of the fuzzy systems are based on the application of two multi-criteria decision-making methods. The AHP method was used to define the mutual relationship of the impact of partial indicators (occurrence, severity, and detectability) on risk. In this way, subjectivity in risk assessment is reduced. In the composition of the fuzzy model, the TOPSIS method is introduced to reduce the dissipation of results, which contributes to the accuracy of the outcome. This contributes to the accuracy of the results. The results were verified through a case study of a complex engineering system—bucket-wheel excavators. The risk was observed from the aspect of the danger of damage and the danger of downtime. The initial information for weak points of ES is defined according to historical damage events and statistics of downtime. Expert knowledge was used for weak points grading in the model. Additional model verification was performed using similar methods, using the same input data. The innovative model, presented in the paper, shows that it is possible to correct different weights of risk indicators. The obtained results show less dispersion compared with other existing methods. Weak points with increased risk have been located, and an algorithm has been proposed for risk-based maintenance application and implementation.

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.

Availability is one of the most used terms in maintainability engineering. This concept is used to denote: The quality of service of an engineering system, i.e., machines, weak points’ analysis, asset management, as well as making decisions in the process of life cycle management. Availability is an overall indicator and contains partial indicators that are oriented towards reliability, maintenance, and logistical support. Availability presents a variable value and changes in time and space. Usually, availability is shown as the coefficient of time use of the machine. This approach is not good enough because it does not go into the structure of the availability itself and requires a high level of IT support in system monitoring. In this sense, this paper will use the fuzzy theory and the corresponding analytic hierarchy process (AHP) multi-criteria analysis to present a conceptual and mathematical model for the assessment of availability based on expert judgment. The model will be shown in the case study (on the example) of bulldozers working in the open-pit lignite mine.

Artificial lift methods have applications in oil wells where oil production is no longer possible due to natural reservoir energy, so this necessary energy is added by introducing lift methods. In order to achieve optimum production, the selection of an artificial lift method is very important. This paper uses fuzzy logic as a mathematical and conceptual model for selection of the optimal artificial lift method. The outcome or IF-THEN rules, as the central part of the model, is based on empirical data from the selected oil fields. Results are presented in two ways: according to the surfaces of irregular geometric bodies, and their gravity with the scattering of results, i.e., on smaller and greater possibilities of interpreting results when there are small differences in outputs. Finally, a sensitivity analysis of the model is presented.

Natural gas is used for the production of almost 20% of total energy today. The natural gas security of the Republic of Serbia is an urgent strategic, political and security issue. Serbia is one of the most vulnerable countries in Southeast Europe, because it only has one supply route. This study is a contribution to efforts to better understand the factors affecting energy security through the implementation of a new methodology based on the fuzzy–AHP synthesis model for measuring energy security. This new methodology was used to identify the energy, economic, environmental, social and technical indicators that accompany energy security analysis. The fuzzy–AHP synthesis model uses the asymmetric fuzzy inference approach for an outcome finding with the asymmetric position of fuzzy sets. The most important characteristic of the proposed model is its ability to operate with numerical and linguistic data and universality of application. The result of the proposed model shows a quantified assessment of energy security and its trend in the future of the natural gas sector. It indicates an unacceptably low level of present energy security and a gas system very vulnerable to supply cuts if the current gas infrastructure remains as it is in the future.