FMEA analysis is a tool of quality improvement that has been widely used for decades. Its classical version prioritizes risk of failure by risk priority number (RPN). The RPN is a product of severity (S), occurrence (O), and detection (D), where all of the factors have equal levels of significance. This assumption is one of the most commonly criticized drawbacks, as it has given unreasonable results for real-world applications. The RPN can produce equal values for combinations of risk factors with different risk implications. Another issue is that of the uncertainties and subjectivities of information employed in FMEA analysis that may arise from lack of knowledge, experience, and employed linguistic terms. Many alternatives of risk assessment methods have been proposed to overcome the weaknesses of classical FMEA risk management in which we can distinguish methods of modification of RPN numbers of employing new tools. In this study, we propose a modification of the traditional RPN number. The main difference is that severity and occurrence are valued based on subfactors. The detection number remained unchanged. Additionally, the proposed method prioritizes risk in terms of implied risk to the systems by implementing functional failures (effects of potential failures). A typical fluid power system was used to illustrate the application of this method. The method showed the correct failure classification, which meets the industrial experience and other research results of failures of fluid power systems.

The main purpose of the work which was carried out and is presented in this paper was to examine the possibility of using fuzzy logic inference for conducting a risk analysis with the help of a sheet-based Failure Mode and Effects Analysis method (FMEA). At the beginning, the main features of the analysed method were presented, with particular emphasis put on the Risk, Priority and Number parameters. Then, a proposal has been made which suggests using Matlab Fuzzy Logic Toolbox package in order to convert the factors into the form of fuzzy sets and to define rules for fuzzy inference process has been made. Finally, the created fuzzy logic model was used to present an example analysis of a turbocharger failure in the fuzzified form.

The main aim of this work was to create a model and carry out simulation tests of a hydraulic system for generating a pressure pulse with strictly defined time parameters. Obtaining a proper pressure course is a key condition for correctness of a long-term testing of hydraulic components durability, including e.g. new types of hoses. The requirements regarding the shape of the impulse were formulated on the basis of the ISO 6803:2008 standard which concerns hydraulic pressure testing of rubber hoses and hose assemblies without flexing. In the first step, a mathematical model of the system was built using equations describing the system geometry, flow equations and flow balances formulated for the separated volumes. Next, a simulation model of the hydraulic system was created in Matlab-Simulink. After obtaining flow characteristics, a model of a required pressure signal generator was built, followed by a fuzzy logic controller created in the Anfis editor of the Fuzzy Logic Toolbox. During the iterative tuning process, parameters of the fuzzy controller were adjusted. Then, the curves of the obtained and the required pressure for different values of the flow rate of the working medium were compared. As arises from the comparison results, the fuzzy logic controller fulfills the requirements and thus may be an advantageous option for generating the pressure signal.

Hydraulic systems are widely used in the aeronautic, machinery, and energy industries. The functions that these systems perform require high reliability, which can be achieved by examining the causes of possible defects and failures and by taking appropriate preventative measures. One of the most popular methods used to achieve this goal is FMEA (Failure Modes and Effects Analysis), the foundations of which were developed and implemented in the early 1950s. It was systematized in the following years and practically implemented. It has also been standardized and implemented as one of the methods of the International Organization for Standardization (ISO) 9000 series standards on quality assurance and management. Apart from wide application, FMEA has a number of weaknesses, which undoubtedly include risk analysis based on the RPN (Risk Priority Number), which is evaluated as a product of severity, occurrence, and detection. In recent years, the risk analysis has been very often replaced by fuzzy logic. This study proposes the use of matrix analysis and statistical methods for performing simplified RCA (Root Cause Analysis) and for classification potential failures for a variable delivery vane pump. The presented methodology is an extension of matrix FMEA and allows for prioritizing potential failures and their causes in relation to functions performed by pump components, the end effects, and the defined symptoms of failure of the vane pump.

In aquaculture, new production technologies are under development and testing. One promising type of technology is the closed floating cage. Egget^® is one of these newly developed technologies, which is egg-shaped and vertically floating. One of the challenges is to determine hydrodynamic loads. Therefore, this study focuses on estimating the resistance and the resistance coefficient for steady flow with various velocities and Reynolds numbers on a scaled model. It includes simulations using Computational Fluid Dynamics (CFD) for two depths and experiments in the MarinLab at Western Norway University of Applied Sciences (HVL). As the cage is partially submerged, the simulations are performed using the Volume of Fluid (VOF) technique for modeling free surface flow. The comparison of experimental and simulation results show good agreement.

Preventive methods are important group of methods used in the process of design and which are known as quality design methods. The aim of these methods is identification of potential failures and cause-and-effect relationships in consistent and systematic way, and then taking appropriate preventive or corrective actions. The well-known examples of preventive methods also used for modelling and analysis of the criticality (risk) factor are FMEA analysis and FTA analysis. A matrix FMEA analysis method has been presented and discussed in the work. The basic assumptions related to this method were characterized and algorithms for each stages of analysis have been presented. It has been presented practical application of FMEA method on example of selected components of hydraulic system.