Deng Entropy Weighted Risk Priority Number Model for Failure Mode and Effects Analysis

Zheng, Haixia; Tang, Yongchuan

doi:10.3390/e22030280

Cited by 26 publications

(19 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, the Deng entropy and evidence distance are utilized in [66]. Deng entropy is adopted for uncertain degree modeling of FMEA experts in [67]. The aforementioned methods do not put emphasis on reconstructing the BPAs.…”

Section: Literature Review a Terminology In Fmeamentioning

confidence: 99%

A Novel Failure Mode and Effects Analysis Model Using Triangular Distribution-Based Basic Probability Assignment in the Evidence Theory

Zheng

Tang

2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

Failure mode and effects analysis (FMEA) is a typical risk assessment and prevention technology, in which different experts provide different assessments on the target system to identify the risk grades of its components. Sometimes, the assessments contain conflict information. How to manage and fuse the conflict assessment information is an open issue. We propose a triangular distribution-based basic probability assignment (TDBPA) method to model and fuse the conflict risk level coming from different experts' assessments in the frame of Dempster-Shafer evidence theory. First, the subjective assessments of risk analysis from domain experts are modeled with belief structure in Dempster-Shafer evidence theory. Then, the assessments are transformed as the TDBPA function. Thirdly, the conflict risk assessments from the FMEA team for failure analysis can be fused with Dempster rule of combination. After that, the modified risk priority number (RPN) model based on fused assessment can be calculated for ranking of failure modes. Finally, recommended actions should be taken for prevention of potential risk items. We verify the rationality and efficiency of the proposed method with a case study in the blades of an aircraft turbine. In short, the presented FMEA methodology procedure in this paper is well organized so that we can apply it in a more simple and understandable way. Utilizing the character of triangular distribution, taking adjacent values into account, TDBPA method can smooth the conflict assessment for information fusion. In addition, the shortcoming of repeating values in classical RPN is eliminated in the proposed method, which improves the ability for risk assessment of FMEA. INDEX TERMS Failure mode and effects analysis (FMEA), Dempster-Shafer evidence theory, basic probability assignment, triangular distribution, failure analysis, knowledge reasoning.

show abstract

Section: Literature Review a Terminology In Fmeamentioning

confidence: 99%

A Novel Failure Mode and Effects Analysis Model Using Triangular Distribution-Based Basic Probability Assignment in the Evidence Theory

Zheng

Tang

2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

show abstract

“…Though FMEA methodology demonstrates good clarity in priority indexing in various cases in which it was applied (Cabanes, Hubac, Masson, & Weil, 2017;Kougioumtzoglou & Lazakis, 2015). However, the methodology lacks transparency in ways risks are considered (Zheng & Tang, 2020). The Risk Priority Number (RPN) in FMEA, is derived as in (1) (Carlson, 2012;Ratnayake, 2012;Stamatis, 2015).…”

Section: *Corresponding Authormentioning

confidence: 99%

A Framework for Sustainable Maintenance of Offshore Energy Structures

Okoro¹,

Adedipe

Lawal

et al. 2020

FUOYEJET

View full text Add to dashboard Cite

This paper proposes a structure for maintenance decision support suitable for application to renewable energy assets. The method combines subjective tacit knowledge of subject-area experts with well-structured Analytical Hierarchical Process (AHP) to elicit weights of criteria relevant for effects evaluation of possible failures modes towards support for component’s maintenance decisions. The Technique for Ordered Preference using Similarity to Ideal Solution (TOPSIS) algorithm is adopted for aggregating the evaluation scores and achieving priority indexing given the conflicting characteristics of some criteria. Part of the highlights of the Framework is the implementation of the group experts, as well as individual expert's elicitations in a complimentary manner that eliminates subjective opinions and achieves a repeatable evaluation score. The conclusion of the analysis is the prioritisation of the component’s failure; An indicative case study of offshore wind turbine jacket support structure is used to demonstrate the applicability of the approach and the analysis results-which shows priority failure modes for focused maintenance intervention as bending of Chord/Brace ( ), collapse of Chord/Brace ( ), buckling of Long piles ( ), and Truss( ), overturning of Skirt pile ( ), and fatigue of Long pile ( ), further demonstrates the capacity of the model to support maintenance decisions. Caution is exercised in the selection of criteria that would capture the objectives of the risk analyses by consulting wide range of industry experts. Keywords— AHP, Expert, Offshore energy, TOPSIS, Wind turbine Support Structure

show abstract

“…Fourth, the evidence in the open world assumption needs further consideration [ 26 , 27 ]. The uncertainty measure including belief entropy can be a promising method for uncertain information modeling, processing, and management of conflict in DS theory [ 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

An Improved Total Uncertainty Measure in the Evidence Theory and Its Application in Decision Making

Qin

Tang

Wen

2020

Entropy

Self Cite

View full text Add to dashboard Cite

Dempster–Shafer evidence theory (DS theory) has some superiorities in uncertain information processing for a large variety of applications. However, the problem of how to quantify the uncertainty of basic probability assignment (BPA) in DS theory framework remain unresolved. The goal of this paper is to define a new belief entropy for measuring uncertainty of BPA with desirable properties. The new entropy can be helpful for uncertainty management in practical applications such as decision making. The proposed uncertainty measure has two components. The first component is an improved version of Dubois–Prade entropy, which aims to capture the non-specificity portion of uncertainty with a consideration of the element number in frame of discernment (FOD). The second component is adopted from Nguyen entropy, which captures conflict in BPA. We prove that the proposed entropy satisfies some desired properties proposed in the literature. In addition, the proposed entropy can be reduced to Shannon entropy if the BPA is a probability distribution. Numerical examples are presented to show the efficiency and superiority of the proposed measure as well as an application in decision making.

show abstract

Deng Entropy Weighted Risk Priority Number Model for Failure Mode and Effects Analysis

Cited by 26 publications

References 71 publications

A Novel Failure Mode and Effects Analysis Model Using Triangular Distribution-Based Basic Probability Assignment in the Evidence Theory

A Novel Failure Mode and Effects Analysis Model Using Triangular Distribution-Based Basic Probability Assignment in the Evidence Theory

A Framework for Sustainable Maintenance of Offshore Energy Structures

An Improved Total Uncertainty Measure in the Evidence Theory and Its Application in Decision Making

Contact Info

Product

Resources

About