Fuzzy based risk prioritisation in an auto LPG dispensing station

Kumar, Akshay; Rajakarunakaran, S.; Pitchipoo, P.; Vimalesan, R.

doi:10.1016/j.ssci.2017.09.011

Cited by 33 publications

(10 citation statements)

References 41 publications

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“…Numerous researchers have incorporated the fuzzy theory into FMEA to express the vague and uncertain information in risk evaluation accurately. [21][22][23] In practical applications, risk-evaluation information is expressed in linguistic terms of a fuzzy set (FS), 24 such as triangular fuzzy numbers, 25 trapezoidal fuzzy numbers, 26,27 intuitionistic fuzzy numbers, 28,29 and interval-valued intuitionistic fuzzy numbers. 30 As the extension of traditional FSs 31 and intuitionistic FSs, 32 single-valued trapezoidal neutrosophic fuzzy sets (SVTNFSs) can express additional uncertain information.…”

Section: Introductionmentioning

confidence: 99%

<p>Evaluating Surgical Risk Using FMEA and MULTIMOORA Methods under a Single-Valued Trapezoidal Neutrosophic Environment</p>

Cheng¹,

Li²,

He³

et al. 2020

RMHP

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Background Human errors during operations may seriously threaten patient recovery and safety and affect the doctor–patient relationship. Therefore, risk evaluation of the surgical process is critical. Risk evaluation by failure mode and effect analysis (FMEA) is a prospective technology that can identify and evaluate potential failure modes in the surgical process to ensure surgical quality and patient safety. In this study, a hybrid surgical risk–evaluation model was proposed using FMEA and multiobjective optimization on the basis of ratio analysis plus full multiplicative form (MULTIMOORA) method under a single-valued trapezoidal neutrosophic environment. This work aimed to determine the most critical risk points during the surgical process and analyze corresponding solutions. Methods A team for FMEA was established from domain experts from different departments in a hospital in Hunan Province. Single-valued trapezoidal neutrosophic numbers (SVTNNs) were used to evaluate potential risk factors in the surgical process. Cmprehensive weights combining subjective and objective weights were determined by the best–worst method and entropy method to differentiate the importance of risk factors. The SVTNN–MULTIMOORA method was utilized to calculate the risk-priority order of failure modes in a surgical process. Results The hybrid FMEA model under the SVTNN–MULTIMOORA method was used to calculate the ranking of severity of 21 failure modes in the surgical process. An unclear diagnosis is the most critical failure in the surgical process of a hospital in Hunan Province. Conclusion The proposed model can identify and evaluate the most critical potential failure modes of the surgical process effectively. In addition, such a model can help hospitals to reduce surgical risk and improve the safety of surgery.

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Section: Introductionmentioning

confidence: 99%

<p>Evaluating Surgical Risk Using FMEA and MULTIMOORA Methods under a Single-Valued Trapezoidal Neutrosophic Environment</p>

Cheng¹,

Li²,

He³

et al. 2020

RMHP

View full text Add to dashboard Cite

show abstract

“…However, this traditional FMEA risk-evaluation approach has often been extensively criticized in extant literature for a variety of reasons [6]. The major shortcomings of the traditional RPN-based approach are as follows: (i) The relative importance among O, S, and D is not considered [7][8][9][10]; (ii) the three risk factors are difficult to precisely evaluate [4,[11][12][13][14][15][16][17]; (iii) interdependencies among various failure modes and effects are not considered [1,5,18,19]; (iv) the method depends on experts' intuition and experience rather than the scientific method to estimate the three risk components [20,21]; and (v) there is no consideration of possible hierarchical relationships among failures [6,22,23].…”

Section: Introductionmentioning

confidence: 99%

“…Many researchers have attempted to improve the RPN-based risk-evaluation method of FMEA. Some researchers have considered facilitating the assessment of the three risk-evaluation factors-O, S, and D-by adopting fuzzy logic-based approaches [4,5,7,10,12,19,[24][25][26] or fuzzy rule-based Bayesian reasoning approaches [27]. Other researchers [9,28] employed both grey and fuzzy theories in FMEA.…”

Section: Introductionmentioning

confidence: 99%

Time-Dependent Probabilistic Model for Hierarchical Structure in Failure Mode and Effect Analysis

Jang

Min

2019

Applied Sciences

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Failure mode and effect analysis (FMEA) is a structured technique for identifying risks that may occur during a given stage of a system’s life cycle. However, the use of the risk priority number (RPN) in traditional FMEA results in difficulties with regard to quantification of the degree of risk in the hierarchical failure structure. This study proposes the use of a hierarchical time-dependent FMEA approach to overcome the limitations encountered during the implementation of traditional FMEA approaches. In place of the RPN, a probabilistic loss model is developed under a hierarchical structure considering the elapsed time from the failure-cause (FC) to the system failure. By assuming exponential and case functions for each occurrence and detection time instant, the expected loss corresponding to each FC can be evaluated. As a result of the practical application of the time-dependent probabilistic model through the numerical example, we could reasonably evaluate the risk from the cause of failure in the hierarchical structure in terms of economic loss.

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“…However, this traditional FMEA risk-evaluation approach has often been extensively criticized in extant literature for a variety of reasons [2]. Noteworthy drawbacks of the traditional RPN-based approach include (i) no consideration of relative importance among O, S, and D parameters [7][8][9][10]; (ii) difficulties involved in precise evaluation of the three risk factors [5,[11][12][13][14][15][16][17]; (iii) no consideration of interdependencies among different failure-causes and the corresponding effects [6,[18][19][20]; and (iv) over-dependence on expert intuition and experience instead of scientific methods for evaluation of the three risk components [21,22].…”

Section: Introductionmentioning

confidence: 99%

“…Many researchers have attempted to overcome the above-mentioned drawbacks, thereby improving the FMEA risk-evaluation method in the process. Liu et al [2] reported that the most popular FMEA approach corresponds to the fuzzy rule-based system [10,[23][24][25], followed by the grey theory [9,10], cost-based model [11][12][13], AHP/ANP [7,19,26,27], and linear programming. Others included an integration-based approach [8,[15][16][17]21,22,28] and probability-based methodology [14,29].…”

Section: Introductionmentioning

confidence: 99%

Time-Dependent Probabilistic Approach of Failure Mode and Effect Analysis

Jang

Min

2019

Applied Sciences

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Failure mode and effect analysis (FMEA) is one of the most widely employed pre-evaluation techniques to avoid risks that may occur during product design and manufacturing phases. However, use of the risk priority number (RPN) in traditional FMEA results in difficulties being encountered with regard to quantification of the degree of risk involved. This study proposes the use of a probabilistic time-dependent FMEA (TD-FMEA) approach to overcome limitations encountered during implementation of traditional FMEA approaches. To this end, the proposed method defines the risk priority metric (RPM) as a priority decision value. RPM corresponds to the product of the expected loss and occurrence rate of the failure-cause. By assuming exponential and case functions for each occurrence and detection time instant, the expected loss corresponding to each failure-cause can be evaluated. Utility of the proposed approach has been described in the light of results obtained via its implementation during an automotive-manufacturing case study performed for the purpose of illustration.

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Fuzzy based risk prioritisation in an auto LPG dispensing station

Cited by 33 publications

References 41 publications

<p>Evaluating Surgical Risk Using FMEA and MULTIMOORA Methods under a Single-Valued Trapezoidal Neutrosophic Environment</p>

<p>Evaluating Surgical Risk Using FMEA and MULTIMOORA Methods under a Single-Valued Trapezoidal Neutrosophic Environment</p>

Time-Dependent Probabilistic Model for Hierarchical Structure in Failure Mode and Effect Analysis

Time-Dependent Probabilistic Approach of Failure Mode and Effect Analysis

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