Fuzzy-FMSA: Evaluating Fault Monitoring and Detection Strategies Based on Failure Mode and Symptom Analysis and Fuzzy Logic

2020 ◽  
Vol 6 (3) ◽  
Author(s):  
Carlos Alberto Murad ◽  
Arthur Henrique de Andrade Melani ◽  
Miguel Angelo de Carvalho Michalski ◽  
Adherbal Caminada Netto ◽  
Gilberto Francisco Martha de Souza ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Failure Mode ◽  
Failure Modes ◽  
Monitoring Techniques ◽  
Knowledge Based ◽  
Diagnosis And Prognosis ◽  
Kaplan Turbine ◽  
Shaft System ◽  
Fmea Method ◽  
Criticality Analysis

Abstract Failure mode and symptoms analysis (FMSA) is a relatively new and still not very much employed variation of failure modes, effects and criticality analysis (FMECA), a technique broadly used in reliability, safety, and quality engineering. While FMECA is an extension of the well-known failure mode and effects analysis (FMEA) method, primarily used when a criticality analysis is required, FMSA focuses on the symptoms produced by each considered failure mode and the selection of the most appropriate detection and monitoring techniques and strategies, maximizing the confidence level in the diagnosis and prognosis. However, in the same way as FMECA and FMEA, FMSA inherits some deficiencies, presenting somewhat biased results and uncertainties intrinsic to its development, due to its own algorithm and the dependence on knowledge-based inputs from experts. Accordingly, this article presents a fuzzy logic application as a complement to FMSA in order to mitigate such uncertainties' effects. As a practical example, the method is applied to a Kaplan turbine shaft system. The monitoring priority number (MPN) obtained through FMSA is compared to the fuzzy monitoring priority number (FMPN) resulting from fuzzy logic application, demonstrating how the proposed method improves the evaluation of detection and monitoring techniques and strategies.

Amalgamated Criticality Analysis Methodology

2013 ◽  
Vol 679 ◽  
pp. 101-106
Author(s):  
Ming Li Liao ◽  
Yung Tsan Jou ◽  
Cheng Shih Liaw
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Design Tool ◽  
Maximal Entropy ◽  
Mode Effects ◽  
Knowledge Based ◽  
Analysis Methodology ◽  
Safety And Reliability ◽  
Mathematical Difficulties ◽  
Criticality Analysis

Failure mode effects and criticality analysis (FMECA) is a widely useful design tool for enhancing product quality, safety and reliability. Most of the current FMECA procedure is in accordance with MIL-STD-1629A by which to conduct FMECA and criticality analysis, which is able to prioritize the failure modes and undertake limited corrective actions toward eliminating product risks. However, the criticality analysis calculation and its interpretation for a failure mode have some mathematical difficulties and erroneous omissions. To resolve these problems, this study proposes a new amalgamated criticality analysis methodology, which is knowledge-based to obtain the four different factor criteria and then using the maximal entropy ordered weighted geometric averaging (ME-OWGA) approach to compute the criticality numbers for a system. This study evaluates criticality analysis in the context of a communication system; the experimental results demonstrate that the proposed method is both accurate and provides discriminating analysis information that helps decision making in product design processes.

scholarly journals Pendekatan Fuzzy FMEA dalam Analisis Faktor Risiko Kecelakaan Kerja

2017 ◽  
Vol 6 (1) ◽  
pp. 29
Author(s):  
Ronald Sukwadi ◽  
Frederikus Wenehenubun ◽  
Tarsina Wati Wenehenubun
Keyword(s):  
Risk Factors ◽  
Fuzzy Logic ◽  
Risk Factor ◽  
Failure Mode ◽  
Failure Modes ◽  
Effect Analysis ◽  
Fuzzy Fmea ◽  
Work Accident ◽  
Work Accidents ◽  
Fmea Method

<p><em>This </em><em>study</em><em> </em><em>aims to</em><em> </em><em>identify and </em><em>analyze </em><em>the </em><em>risk factors </em><em>of</em><em> work accidents</em><em>. </em><em>Failure Mode and Effect Analysis (FMEA) and Fuzzy Logic </em><em>approach are applied</em><em>. </em><em>The information obtained from the workers is expressed using fuzzy linguistics terms, and a FMEA method is proposed to determine the risk priority of failure modes. </em><em>The results </em><em>indicate</em><em> that </em><em>injuries caused when struck by an object are the highest</em><em> risk factor </em><em>of work accident (</em><em>FRPN </em><em>=</em><em> 886</em><em>). Some work improvements are suggested to reduce or eliminate the work risks.</em><em></em></p><p><em>Keywords</em><em>: Risk factor</em><em>s</em><em>, work accident, FMEA, Fuzzy </em></p>

Fuzzy risk assessment for electro-optical target tracker

2016 ◽  
Vol 33 (6) ◽  
pp. 830-851 ◽  
Author(s):  
Soumen Kumar Roy ◽  
A K Sarkar ◽  
Biswajit Mahanty
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Linear Equations ◽  
Mode Analysis ◽  
Failure Behavior ◽  
Membership Functions ◽  
Design And Development ◽  
Effect Analysis ◽  
Content Type ◽  
Criticality Analysis

Purpose – The purpose of this paper is to evolve a guideline for scientists and development engineers to the failure behavior of electro-optical target tracker system (EOTTS) using fuzzy methodology leading to success of short-range homing guided missile (SRHGM) in which this critical subsystems is exploited. Design/methodology/approach – Technology index (TI) and fuzzy failure mode effect analysis (FMEA) are used to build an integrated framework to facilitate the system technology assessment and failure modes. Failure mode analysis is carried out for the system using data gathered from technical experts involved in design and realization of the EOTTS. In order to circumvent the limitations of the traditional failure mode effects and criticality analysis (FMECA), fuzzy FMCEA is adopted for the prioritization of the risks. FMEA parameters – severity, occurrence and detection are fuzzifed with suitable membership functions. These membership functions are used to define failure modes. Open source linear programming solver is used to solve linear equations. Findings – It is found that EOTTS has the highest TI among the major technologies used in the SRHGM. Fuzzy risk priority numbers (FRPN) for all important failure modes of the EOTTS are calculated and the failure modes are ranked to arrive at important monitoring points during design and development of the weapon system. Originality/value – This paper integrates the use of TI, fuzzy logic and experts’ database with FMEA toward assisting the scientists and engineers while conducting failure mode and effect analysis to prioritize failures toward taking corrective measure during the design and development of EOTTS.

Failure mode, effects and criticality analysis improvement by using new criticality assessment and prioritization based approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ammar Chakhrit ◽  
Mohammed Chennoufi
Keyword(s):  
Failure Mode ◽  
Conventional Method ◽  
Fuzzy Inference System ◽  
Risk Evaluation ◽  
Failure Modes ◽  
Fuzzy Inference ◽  
Decision Makers ◽  
Inference System ◽  
Content Type ◽  
Criticality Analysis

Purpose This paper aims to enable the analysts of reliability and safety system to assess the criticality and prioritize failure modes perfectly to prefer actions for controlling the risks of undesirable scenarios. Design/methodology/approach To resolve the challenge of uncertainty and ambiguous related to the parameters, frequency, non-detection and severity considered in the traditional approach failure mode effect and criticality analysis (FMECA) for risk evaluation, the authors used fuzzy logic where these parameters are shown as members of a fuzzy set, which fuzzified by using appropriate membership functions. The adaptive neuro-fuzzy inference system process is suggested as a dynamic, intelligently chosen model to ameliorate and validate the results obtained by the fuzzy inference system and effectively predict the criticality evaluation of failure modes. A new hybrid model is proposed that combines the grey relational approach and fuzzy analytic hierarchy process to improve the exploitation of the FMECA conventional method. Findings This research project aims to reflect the real case study of the gas turbine system. Using this analysis allows evaluating the criticality effectively and provides an alternate prioritizing to that obtained by the conventional method. The obtained results show that the integration of two multi-criteria decision methods and incorporating their results enable to instill confidence in decision-makers regarding the criticality prioritizations of failure modes and the shortcoming concerning the lack of established rules of inference system which necessitate a lot of experience and shows the weightage or importance to the three parameters severity, detection and frequency, which are considered to have equal importance in the traditional method. Originality/value This paper is providing encouraging results regarding the risk evaluation and prioritizing failures mode and decision-makers guidance to refine the relevance of decision-making to reduce the probability of occurrence and the severity of the undesirable scenarios with handling different forms of ambiguity, uncertainty and divergent judgments of experts.

scholarly journals Parameters Assessment of the FMEA Method by Means of Fuzzy Logic

2018 ◽  
Vol 2 (Special edition 2) ◽  
pp. 123-132
Author(s):  
Jasminka Bonato ◽  
Martina Badurina ◽  
Julijan Dobrinić
Keyword(s):  
Fuzzy Logic ◽  
Failure Analysis ◽  
Failure Mode ◽  
Mathematical Function ◽  
Analysis Method ◽  
Effect Analysis ◽  
New Approach ◽  
System Failures ◽  
Numerical Indicator ◽  
Fmea Method

The paper aims at presenting the FMEA method based on the fuzzy technique, representing a new approach to the failure analysis and its effects on the observed system. The FMEA (Failure Mode and Effect Analysis) method has assigned the risks a coefficient i.e. a numerical indicator that very clearly defines the degree of risk. The risk is calculated as a mathematical function of RPN which depends on the effects S, probability O that some case will lead to a failure and to a probability that a failure D can not be detected before its effects are realized. RPN = S O D. The FMEA method, based on the fuzzy logic, makes a more reliable evaluation of the observed system failures possible.

Failure Mode and Effect Analysis (FMEA) for Enhancing Reliability of Water Tube Boiler in Thermal Power Plant

2016 ◽  
Vol 8 (02) ◽  
pp. 79-86
Author(s):  
Kapil Dev Sharma ◽  
Shobhit Srivastava
Keyword(s):  
Power Plant ◽  
Failure Mode ◽  
Thermal Power Plant ◽  
Failure Modes ◽  
Thermal Power ◽  
Effect Analysis ◽  
Water Tube ◽  
Potential Failure ◽  
Fmea Method ◽  
Continuous Power

Failure mode and effect analysis is one of the QS-9000 quality system requirement supplements, with a wide applicability in all industrial fields. FMEA is the inductive failure analysis instruments which can be defined as a methodical group of activities intended to recognize and evaluate the potential failure modes of a product/ process and its effects with an aim to identify actions which could eliminate or reduce the chance of the potential failure before the problem occur. The purpose of this paper is to evaluate the FMEA research and application in the Thermal Power Plant Industry. The research will highlight the application of FMEA method to water tubes (WT) in boilers with an aim to find-out all the major and primary causes of boiler failure and reduce the breakdown for continuous power generation in the plant. Failure Mode and Effect Analysis technique is applied on most critical or serious parts (components) of the plant which having highest Risk Priority Number (RPN). Comparison is made between the quantitative results of FMEA and reliability field data from real tube systems. These results are discussed to establish relationships which are useful for future water tube designs.

scholarly journals Assessing the Risks of Airport Airside through the Fuzzy Logic-Based Failure Modes, Effect, and Criticality Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Cheng-Min Feng ◽  
Chi-Chun Chung
Keyword(s):  
Risk Assessment ◽  
Fuzzy Logic ◽  
Failure Modes ◽  
Threshold Value ◽  
Civil Aviation ◽  
Aviation Accidents ◽  
Decision Factors ◽  
Modeling Process ◽  
Assessment Matrix ◽  
Criticality Analysis

To identify risk items, measure risk value objectively, and establish risk assessment matrix of airports is the major task of airport safety. This paper first extracts 14 risk items of airports from the International Civil Aviation Organization (ICAO) aviation accidents database and then applies Failure Modes, Effect and Criticality Analysis (FMECA) to define the decision factors of probability, severity and detectability of airport risks. This paper also designs a questionnaire and applies fuzzy logic to discover the importance of decision factors, to find out the threshold value of Risk Assessment Matrix, and to prioritize the airport risks. This paper uses Taiwan Taoyuan International Airport as a case study to demonstrate the modeling process and analyze the results.

Application of Fuzzy Logic in Design Failure Mode and Effects Analysis

2013 ◽  
Vol 371 ◽  
pp. 832-836 ◽  
Author(s):  
Nadia Belu ◽  
Daniel Constantin Anghel ◽  
Nicoleta Rachieru
Keyword(s):  
Fuzzy Logic ◽  
Failure Mode ◽  
Automotive Industry ◽  
Failure Modes ◽  
Fuzzy Model ◽  
Potential Problems ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Promising Solution ◽  
Potential Risks

Failure Mode and Effects Analysis (FMEA) is one of the basic and the most used techniques of quality management that is used for continuous improvements in product or process designs. While applying this technique, determining the Risk Priority Numbers (RPN), which indicate the levels of risks associated with potential problems, is of prime importance for the success of application. A traditional RPN is obtained as product of three risk factors: occurrence, severity and detection. Values of these factors are generally attained from past experience and this way of risk assessment sometimes leads to inconsistencies and inaccuracies during priority numbering. Fuzzy logic approach is considered a promising solution in order to give a more accurate ranking of potential risks. This paper presented a fuzzy model, in order to assess and rank risks associated to failure modes that could appear in the functioning of a headlining product used in automotive industry.

Failure Mode, Effect and Criticality Analysis of CNC Grinder

2011 ◽  
Vol 141 ◽  
pp. 284-288
Author(s):  
Hong Jun Wang ◽  
Lei Sun ◽  
Lei Shi
Keyword(s):  
Failure Mode ◽  
Production Line ◽  
Failure Modes ◽  
Mode Effect ◽  
Technical Basis ◽  
Criticality Analysis ◽  
Fault Record

CNC grinder is considered as the key equipment of camshaft production line. Its reliability directly influences the quality of the products. This article takes an analysis of fault record of 15 sets of CNC grinders of production line, gets failure positions analysis, and then reaches data of failure modes, fault reason of CNC grinder. Comprehensive analyses of criticality for the machine are done through establishing models. Therefore, this analysis provides technical basis for repair, maintenance and update of CNC grinder of camshaft production line.

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