A risk evaluation and prioritization method for FMEA with prospect theory and Choquet integral

Wang, Weizhong; Liu, Xinwang; Qin, Yong; Fu, Yong

doi:10.1016/j.ssci.2018.08.009

Cited by 141 publications

(86 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…in systems, designs, processes, and services prior to them being made accessible to customers [1]. Since its introduction as an analysis tool for failure mitigation, FMEA has been extensively used in a wide range of industrial applications, including, but not limited to, automotive, semiconductor design, aerospace and aviation, healthcare, and steel manufacturing applications [2][3][4][5]. In traditional FMEA approaches, the risk associated with an FC is usually evaluated using the risk priority number (RPN), which corresponds to the mathematical product of the occurrence (O), severity (S), and detection (D) of an FC.…”

Section: Introductionmentioning

confidence: 99%

“…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%

See 2 more Smart Citations

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

Jang

Min

2019

Applied Sciences

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Jang

Min

2019

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…The results of the FMEA can help analysts to identify and correct the failure modes that have a detrimental effect on the system and improve its performance during the stages of design and production [2]. Since its introduction as an analysis tool for reducing failures, FMEA has been extensively used in a wide range of industries, including automotive, semiconductor, aircraft medical, and steel industries [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

“…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%

Time-Dependent Probabilistic Approach of Failure Mode and Effect Analysis

Jang

Min

2019

Applied Sciences

View full text Add to dashboard Cite

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.

show abstract

Consensus building in linguistic failure mode and effect analysis: A perspective based on prospect theory

Fan

Zhu

Wei

et al. 2020

Quality & Reliability Eng

View full text Add to dashboard Cite

As one of many scientific and efficient risk assessment approaches, failure mode and effect analysis (FMEA) has been widely applied across various fields. There are two core issues in the FMEA approach: identifying the latent failure modes of the systems, products, processes and services and the risk assessment and the prioritization of those failure modes. Then, corrective measures must be taken in a timely and accessible manner to prevent the occurrence of failure modes with higher risk levels. In practice, several FMEA members from different fields are usually involved in the FMEA implementation process; the risk assessment information given by them may vary greatly. Therefore, it is necessary to integrate a consensus-building process into FMEA. Meanwhile, the psychological behaviours of FMEA members have had a great impact on the final prioritization of failure modes. Prospect theory is an effective approach for describing individual psychological behaviours. Therefore, this paper presents a novel linguistic FMEA approach to address the consensus issue from the perspective of prospect theory. In the proposed linguistic FMEA approach, a consensus measurement approach based on prospect theory is constructed. Then, a novel feedback adjustment mechanism is designed in which FMEA members can adjust not only their assessment information but also their reference points to achieve an acceptable consensus degree. Eventually, a practical application is used to show the validity and applicability of the proposed linguistic FMEA approach.

show abstract

A risk evaluation and prioritization method for FMEA with prospect theory and Choquet integral

Cited by 141 publications

References 32 publications

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

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

Time-Dependent Probabilistic Approach of Failure Mode and Effect Analysis

Consensus building in linguistic failure mode and effect analysis: A perspective based on prospect theory

Contact Info

Product

Resources

About