Evaluating the risk of healthcare failure modes using interval 2-tuple hybrid weighted distance measure

Liu, Hu‐Chen; You, Jing; You, Xiao‐Yue

doi:10.1016/j.cie.2014.07.018

Cited by 89 publications

(57 citation statements)

References 44 publications

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“…the degree of similarity between the jth largest interval 2-tupleã rðjÞ and the meanl (Liu et al 2014d), where rð1Þ; rð2Þ; . .…”

Section: Interval 2-tuple Linguistic Variablesmentioning

confidence: 99%

“…. ; x n ð Þ T , with x j 2 0; 1 ½ and R n j¼1 x j ¼ 1, according to the following formula (Liu et al 2014d): …”

Section: Interval 2-tuple Linguistic Hybrid Weighted Distance Measurementioning

confidence: 99%

“…. ; n ð Þ be a set of interval 2-tuples, then the interval 2-tuple arithmetic mean is computed as (Liu et al 2014d): is called the interval 2-tuple distance (ITD) betweenã andb (Liu et al 2014d). …”

Section: Interval 2-tuple Linguistic Variablesmentioning

confidence: 99%

“…Moreover, via this method, decision makers can express their preferences by the use of linguistic term sets with different granularity of uncertainty. Therefore, Liu et al (2014d) proposed a new risk priority model using interval 2-tuple hybrid weighted distance (ITHWD) measure to overcome the limitations and improve the performance of the traditional FMEA. The new model can not only handle the diversified and uncertain assessments provided by FMEA team members, but also consider the subjective and objective weights of risk factors in the prioritization of the failure modes identified in FMEA.…”

mentioning

confidence: 99%

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FMEA Using Interval 2-Tuple Hybrid Weighted Distance Measure

Liu

2016

FMEA Using Uncertainty Theories and McDm Methods

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The interval 2-tuple linguistic representation method (Zhang 2012) is a useful computational model for computing with words, which has the capability of expressing different types of decision makers' assessment information and has been widely used in many real-world engineering and management problems. Moreover, via this method, decision makers can express their preferences by the use of linguistic term sets with different granularity of uncertainty. Therefore, Liu et al. (2014d) proposed a new risk priority model using interval 2-tuple hybrid weighted distance (ITHWD) measure to overcome the limitations and improve the performance of the traditional FMEA. The new model can not only handle the diversified and uncertain assessments provided by FMEA team members, but also consider the subjective and objective weights of risk factors in the prioritization of the failure modes identified in FMEA. Particularly, the proposed FMEA has exact characteristic and can avoid information distortion and loss in the linguistic information processing.

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“…the degree of similarity between the jth largest interval 2-tupleã rðjÞ and the meanl (Liu et al 2014d), where rð1Þ; rð2Þ; . .…”

Section: Interval 2-tuple Linguistic Variablesmentioning

confidence: 99%

“…. ; x n ð Þ T , with x j 2 0; 1 ½ and R n j¼1 x j ¼ 1, according to the following formula (Liu et al 2014d): …”

Section: Interval 2-tuple Linguistic Hybrid Weighted Distance Measurementioning

confidence: 99%

Section: Interval 2-tuple Linguistic Variablesmentioning

confidence: 99%

mentioning

confidence: 99%

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FMEA Using Interval 2-Tuple Hybrid Weighted Distance Measure

Liu

2016

FMEA Using Uncertainty Theories and McDm Methods

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“…Under the interval 2-tuple linguistic environment, the reference sequence denoted as r * = r * 1 , r * 2 , ..., r * m T can be defined as follows [43]:…”

Section: Determine the Importance Weights Of Crsmentioning

confidence: 99%

Uncertain Quality Function Deployment Using a Hybrid Group Decision Making Model

2016

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Quality function deployment (QFD) is a widely used quality system tool for translating customer requirements (CRs) into the engineering design requirements (DRs) of products or services. The conventional QFD analysis, however, has been criticized as having some limitations such as in the assessment of relationships between CRs and DRs, the determination of CR weights and the prioritization of DRs. This paper aims to develop a new hybrid group decision-making model based on hesitant 2-tuple linguistic term sets and an extended QUALIFLEX (qualitative flexible multiple criteria method) approach for handling QFD problems with incomplete weight information. First, hesitant linguistic term sets are combined with interval 2-tuple linguistic variables to express various uncertainties in the assessment information of QFD team members. Borrowing the idea of grey relational analysis (GRA), a multiple objective optimization model is constructed to determine the relative weights of CRs. Then, an extended QUALIFLEX approach with an inclusion comparison method is suggested to determine the ranking of the DRs identified in QFD. Finally, an analysis of a market segment selection problem is conducted to demonstrate and validate the proposed QFD approach.

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A new risk prioritization model for failure mode and effects analysis

Anes

Henriques

Freitas

et al. 2018

Quality & Reliability Eng

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Failure modes and effects analysis is a framework that has been widely used to improve reliability by prioritizing failures modes using the so‐called risk priority number. However, the risk priority number has some problems frequently pointed out in literature, namely its non‐injectivity, non‐surjectivity, and the impossibility to give weights to risk variables. Despite these disadvantages, the risk priority number continues to be widely used due to its higher simplicity when compared with other alternatives found in literature. In this paper, we propose a novel risk prioritization model to overcome the major drawbacks of the risk priority number. The model contains 2 functions, the risk isosurface function that prioritizes 3 risk variables considering their order of importance in a given risk scenario, and the risk prioritization index function which prioritizes 3 risk variables considering their weights. The novelty of the proposed model is its injectivity, surjectivity, and ease of use in failure modes prioritization. The performance of the proposed model was analyzed using some examples typically used to discuss the conventional risk priority number shortcomings. The model was applied to a case study and its performance correlated with other risk prioritization models. Results show that the failure modes prioritization reached with the proposed model agrees with the expectations made for the risk scenario.

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Evaluating the risk of healthcare failure modes using interval 2-tuple hybrid weighted distance measure

Cited by 89 publications

References 44 publications

FMEA Using Interval 2-Tuple Hybrid Weighted Distance Measure

FMEA Using Interval 2-Tuple Hybrid Weighted Distance Measure

Uncertain Quality Function Deployment Using a Hybrid Group Decision Making Model

A new risk prioritization model for failure mode and effects analysis

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