A FMEA based novel intuitionistic fuzzy approach proposal: Intuitionistic fuzzy advance MCDM and mathematical modeling integration

Yener, Yelda; Can, Gülin Feryal

doi:10.1016/j.eswa.2021.115413

Cited by 36 publications

(15 citation statements)

References 60 publications

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“…By employing fuzzy logic, it is possible to minimize the effects caused by subjective judgments used in the calculation and reduce the fragility of risk analysis, thereby aiding in decision-making (Kutlu and Ekmekçioǧlu, 2012). Some advantages highlighted in the literature when applying fuzzy in conjunction with the FMEA methodology are as follows: the previously linear relationship between the indices S, O, D becomes non-linear; it is possible to assign more significant values to the factors, ensuring that effects with low RPN are not overlooked and are thoroughly analyzed; combinations of the factors (S, O, D) are modeled, resolving situations where the RPN fails to reflect the true risk of failure; fuzzy techniques can incorporate human knowledge, where information is described in vague and imprecise statements; in fuzzy logic, information can be expressed in a language that is easily interpretable (Kumar and Parameshwaran, 2019;Yener and Can, 2021;Ouyang et al, 2022).…”

Section: Integrating Fuzzy Logic and Fmeamentioning

confidence: 99%

Proposal of a facilitating methodology for fuzzy FMEA implementation with application in process risk analysis in the aeronautical sector

Resende,

Dedini,

Eckert

et al. 2023

IJQRM

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PurposeThis study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.Design/methodology/approachBased on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.FindingsThe results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.Practical implicationsThis study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.Originality/valueThis paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

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Section: Integrating Fuzzy Logic and Fmeamentioning

confidence: 99%

Proposal of a facilitating methodology for fuzzy FMEA implementation with application in process risk analysis in the aeronautical sector

Resende,

Dedini,

Eckert

et al. 2023

IJQRM

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show abstract

“…To handle this, Atanassov [2] , [3] proposed the intuitionistic fuzzy sets (IFS), by allocating a non-membership grade in addition to the grade of membership. The IFS has been widely utilized to model several MCDM models [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] . Tao et al [13] provided an algorithm for dynamic group MCDM adapted from the alternative queuing model using intuitionistic fuzzy data by introducing an induced ordered weighted average operator.…”

Section: Background Studymentioning

confidence: 99%

An MCDM approach based on some new Pythagorean cubic fuzzy Frank Muirhead mean operators

Kakati¹

2022

Heliyon

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“…1 While the FMEA method has contributed significantly to risk management, it exhibits notable limitations, particularly in its reliance on precise numerical values for risk assessment, leading many scholars to develop new approaches for FMEA. [2][3][4][5][6][7] First, let us consider the traditional FMEA, which is based on numerical evaluations of decision makers (DMs). A drawback of this approach is the potentially questionable results, as the assessment of failures largely relies on individual DMs' personal experience and domain-specific knowledge, which introduces an element of subjectivity into the process.…”

Section: Introductionmentioning

confidence: 99%

“…Interested readers are referred to. 1,2,6,10,12,13 The innovative contribution of this study lies in its unique implementation of Intuitionistic Fuzzy (IF) principles in conjunction with the MARCOS method for prioritization of failures. As there is a growing recognition of the importance of integrating diverse expert opinions in a more objective and systematic manner, in this study, each DM is assigned a specific weight in the decision-making process, guided by predefined rules.…”

Section: Introductionmentioning

confidence: 99%

A novel method for weighting decision makers for failure mode and effect analysis under intuitionistic fuzzy environment

Akkus,

Testik

2024

Quality & Reliability Eng

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This study introduces an innovative method to implement Failure Mode and Effect Analysis (FMEA) in an Intuitionistic Fuzzy (IF) environment and targets inherent limitations of traditional FMEA, particularly its reliance on precise numerical values that can lead to human subjectivity and compromise accuracy of analysis. The primary aim is to increase the objectivity in evaluating Failure Modes (FMs) in industrial settings, thus enhancing safety and quality assessments. The novel approach integrates the Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) method within an IF framework. An implementation at a defense industry company is performed for evaluation of the FMs by four Decision Makers (DMs), each possessing different levels of experience and system knowledge. A key innovation of this study is the unique weighting methodology applied to DMs, based on predefined rules, which acknowledges and quantifies their varied expertise and insights. Our methodology significantly contributes to the study's practicality and significance in ranking FMs, emphasizing its effectiveness, robustness, and accuracy. The findings reveal that this method greatly reduces the subjectivity found in traditional FMEA, also providing a more detailed and reliable assessment. This is achieved by adapting the analysis to the specific knowledge levels of the DMs, leading to more dependable and objective quality evaluations in industrial processes. The application of this method in the real‐world setting demonstrates its practical relevance and potential for wider adoption.

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A FMEA based novel intuitionistic fuzzy approach proposal: Intuitionistic fuzzy advance MCDM and mathematical modeling integration

Cited by 36 publications

References 60 publications

Proposal of a facilitating methodology for fuzzy FMEA implementation with application in process risk analysis in the aeronautical sector

Proposal of a facilitating methodology for fuzzy FMEA implementation with application in process risk analysis in the aeronautical sector

An MCDM approach based on some new Pythagorean cubic fuzzy Frank Muirhead mean operators

A novel method for weighting decision makers for failure mode and effect analysis under intuitionistic fuzzy environment

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