Risk prioritization in Failure Mode and Effects Analysis using interval type-2 fuzzy sets

Bozdag, Erhan; Asan, Umut; Soyer, Ayberk; Serdarasan, Şeyda

doi:10.1016/j.eswa.2015.01.015

Cited by 97 publications

(43 citation statements)

References 57 publications

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“…Traditional FMEA evaluates hazards by using the risk priority number (RPN), which is a combination parameter of the risk factors occurrence (O), severity of the event (S) and the probability of detection before the risk (D). However, there are some limitations and problems within the FMEA method, like O, S and D, and the RPN method has some weakness in term of accuracy such as small variation in a sub-factor may cause significantly different results (Liu et al, 2015;Bozdag et al, 2015). To deal with this weakness, many studies tried to modify the FMEA method.…”

Section: Literature Reviewmentioning

confidence: 99%

Using Robust-DEA optimization approach to analyze performance and efficiency of a mine in north of Iran

Rabbani¹,

Farrokhi-Asl²,

Manavizadeh³

2017

10.5267/j.msl

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Performance of mines can be affected by different factors such as safety and economic factors. This study aims to analyze the influence of safety and economic factors on mines' performance. To this purpose, a framework is proposed based on a Data Envelopment Analysis (DEA), Robust Data Envelopment Analysis (RDEA) and common weight Robust Data Envelopment Analysis (CWRDEA) to determine the factors affecting on performance of mines. In this study, for the first time, integrated economic and safety factors are considered for evaluation of mines performance. To analyze safety and economic factors, this research gathers real data from a mine with 56 sites in south of Iran. Based on different DEA models, different sites become the best site among other sites, but RDEA is much closer to real situation than basic DEA and CWRDEA is the most efficient approach in real situation.

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Section: Literature Reviewmentioning

confidence: 99%

Using Robust-DEA optimization approach to analyze performance and efficiency of a mine in north of Iran

Rabbani¹,

Farrokhi-Asl²,

Manavizadeh³

2017

10.5267/j.msl

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“…Bozdag et al (2015) further develop a failure mode assessment and prioritization model based on fuzzy logic that both incorporates individual and consensus judgment into a risk rating (Bozdag, Asan, Soyer, & Serdarasan, 2015). As innovative as this model is, there is almost no literature available that illustrates wherein FMEA/FMECA human variability is most prevalent.…”

Section: Fmea and Fmeca As A Risk Management Toolmentioning

confidence: 99%

“…However, as noted by Bozdag et al (2015) very little research has been focused on understanding uncertainty and variations ratings amongst experts (Bozdag, Asan, Soyer, & Serdarasan, 2015). Bozdag et al (2015) further develop a failure mode assessment and prioritization model based on fuzzy logic that both incorporates individual and consensus judgment into a risk rating (Bozdag, Asan, Soyer, & Serdarasan, 2015).…”

Section: Fmea and Fmeca As A Risk Management Toolmentioning

confidence: 99%

“…The analysis is accomplished by analyzing failure modes, or technical risks that are reasonably likely to occur, along with their associated consequences (or severity). In methodologies such as Reliability Centered Maintenance (RCM), it is further extended to develop mitigation strategies (Bozdag, Asan, Soyer, & Serdarasan, 2015).…”

Section: Fmea and Fmeca As A Risk Management Toolmentioning

confidence: 99%

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Building Evidence the Federal Aviation Administration's UAS Safety Strategy Needs Improvement

Wallace¹,

Haritos²,

Robbins³

2018

IJAAA

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“…Risk priority number (RPN) is a popular way to evaluate risk priority in traditional FMEA [19][20][21]. RPN is usually expressed as : PRN = O × S × D, where O, S, and D are three main risk factors which denote the occurrence (O) of a failure mode, the severity (S) of a failure effect, and the probability of not being detected (D), respectively [22].…”

Section: Introductionmentioning

confidence: 99%

Risk Evaluation in Failure Mode and Effects Analysis Using Fuzzy Measure and Fuzzy Integral

2017

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Failure mode and effects analysis (FMEA) is a popular and useful approach applied to examine potential failures in different products, designs, processes, and services. As a vital index, the risk priority number (RPN) can determine the risk priorities of failure modes by some risk factors such as occurrence (O), severity (S), and detection (D). However, in FMEA, the traditional risk priority number approach has some shortcomings, especially in setting the weight of risk factors. This paper presents an improved risk priority number approach based on a fuzzy measure and fuzzy integral. A fuzzy measure is used to reflect the importance of the individual indicators and the indicator set and a fuzzy integral is a nonlinear function defined on the basis of fuzzy measure. The weights of risk factors given by domain experts are seen as fuzzy densities to generate a λ-fuzzy measure which can reflect the weights' difference and relevance about risk factors. Then, the Choquet integral is used to fuse every value of risk factors about failure modes so as to obtain the comprehensive evaluation result. The result can reflect the comprehensive risk level, so it has a definite physical significance. Finally, an illustrative example and a comparison with another approach are given to show the effectiveness of the proposed approach in the paper.

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Risk prioritization in Failure Mode and Effects Analysis using interval type-2 fuzzy sets

Cited by 97 publications

References 57 publications

Using Robust-DEA optimization approach to analyze performance and efficiency of a mine in north of Iran

Using Robust-DEA optimization approach to analyze performance and efficiency of a mine in north of Iran

Building Evidence the Federal Aviation Administration's UAS Safety Strategy Needs Improvement

Risk Evaluation in Failure Mode and Effects Analysis Using Fuzzy Measure and Fuzzy Integral

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