Matrix Fmea Analysis as a Preventive Method for Quality Design of Hydraulic Components

Fabiś-Domagała, Joanna; Momeni, Hassan; Domagała, Mariusz; Filo, Grzegorz

doi:10.2478/czoto-2019-0087

Cited by 7 publications

(6 citation statements)

References 18 publications

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“…A fuzzy model was created in Anfis editor and then was used to analyse a selected turbocharger defect. The obtained RPN values are higher than those from the classical FMEA method [17]: RPN = 224, and RPN = 120, before and after the repair, respectively. However, in both cases the RPN value was approximately halved.…”

Section: Resultscontrasting

confidence: 54%

“…As a practical example will be presented application of the proposed fuzzy model in the analysis of a selected turbocharger defect, resulting in decrease in engine power [17]. The visible symptoms of the fault were noise and vibrations, hence the following factor values were assigned: S = 7, O = 8, D = 4.…”

Section: Practical Application Of Created Fuzzy Fmea Modelmentioning

confidence: 99%

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The idea of fuzzy logic usage in a sheet-based FMEA analysis of mechanical systems

et al. 2018

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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.

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Section: Resultscontrasting

confidence: 54%

Section: Practical Application Of Created Fuzzy Fmea Modelmentioning

confidence: 99%

The idea of fuzzy logic usage in a sheet-based FMEA analysis of mechanical systems

et al. 2018

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“…This can be achieved by establishing the causal relationships of potential product defects taking into account risk factors. This allows for continuous improvement of the product and/or process through regular analysis and making corrections to eliminate the causes of defects and improve product properties (Fabiś-Domagała J. et al, 2019a;Fabiś-Domagała J. et al, 2019b).…”

Section: Introductionmentioning

confidence: 99%

Using the fmea method as a response to a customer complaint: a case study

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Kozina

et al. 2021

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One of the most popular quality management methods is FMEA (Failure mode and effects analysis), which is used to analyze the risk of defects in the product or process in order to eliminate them even before they occur. Its effective implementation reduces the costs of elimination of defects, which increase exponentially in subsequent processes of product implementation. FMEA is most often used where highly complex products are manufactured or where production is a multi-stage process and many departments are involved. The aim of the article was to use the PFMEA to assess the quality of window guides and to improve their quality. This analysis was carried out based on complaints of the main business partner and helped to indicate the main cause for the complaint, identify the corrective actions and check the effectiveness of the proposed corrective actions. The analysis helped avoid similar problems in related products produced on the same production line.

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“…This paper presents an implementation of matrix FMEA analysis [2] for directional flow control valve. There are presented three approaches of matrix FMEA analysis for the valve which allows to identify failures [3,4] and its causes in more details [5][6][7]. This paper also shows that FMEA analysis strongly depends on input data and in any case should be supported by knowledge base which should include as rich as possible information about analyzed problem.…”

Section: Introductionmentioning

confidence: 99%