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

Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 280 ◽  
Author(s):  
Haixia Zheng ◽  
Yongchuan Tang

Failure mode and effects analysis (FMEA), as a commonly used risk management method, has been extensively applied to the engineering domain. A vital parameter in FMEA is the risk priority number (RPN), which is the product of occurrence (O), severity (S), and detection (D) of a failure mode. To deal with the uncertainty in the assessments given by domain experts, a novel Deng entropy weighted risk priority number (DEWRPN) for FMEA is proposed in the framework of Dempster–Shafer evidence theory (DST). DEWRPN takes into consideration the relative importance in both risk factors and FMEA experts. The uncertain degree of objective assessments coming from experts are measured by the Deng entropy. An expert’s weight is comprised of the three risk factors’ weights obtained independently from expert’s assessments. In DEWRPN, the strategy of assigning weight for each expert is flexible and compatible to the real decision-making situation. The entropy-based relative weight symbolizes the relative importance. In detail, the higher the uncertain degree of a risk factor from an expert is, the lower the weight of the corresponding risk factor will be and vice versa. We utilize Deng entropy to construct the exponential weight of each risk factor as well as an expert’s relative importance on an FMEA item in a state-of-the-art way. A case study is adopted to verify the practicability and effectiveness of the proposed model.

Author(s):  
Nikola Komatina ◽  
Danijela Tadić ◽  
Aleksandar Aleksić ◽  
Nikola Banduka

The change of market’s demand could be predictable to a certain degree at stable conditions but it may vary due to disruptive events. This research contributes by establishing the improvement of PFMEA (Process Failure Mode and Effect Analysis) analysis in the domain of assessment and determining severity risk factor, as well as identifying of failure priority. According to the researchers’ and practitioners’ suggestions, severity needs to be considered from the multiple aspects. The risk factor severity is considered from the aspects of product importance, quality, and cost. These aspects have different relative importance, which is determined in an exact way. The relative importance of the aspects, as well as the values of the risk factors, was described by linguistic expressions that are modeled by using the Interval type-2 trapezoidal fuzzy numbers (IT2TrFNs). IT2FBWM was used to determine weight vectors of risk factors. The priority of failures is determined according to the Action priority model which proposed by AIAG & VDA (Automotive Industry Action Group and German Association of the Automotive Industry). The proposed methodology is tested in a Case study where the real-life data originated from a company from the Republic of Serbia that operates as a part of an automotive supply chain.


Author(s):  
F. Dinmohammadi ◽  
M. Shafiee

Failure Mode and Effects Analysis (FMEA) has been extensively used by wind turbine assembly manufacturers for risk and reliability analysis. However, several limitations are associated with its implementation in offshore wind farms: (i) the failure data gathered from SCADA system is often missing or unreliable, and hence, the assessment information of the three risk factors (i.e., severity, occurrence, and fault detection) are mainly based on experts’ knowledge; (ii) it is rather difficult for experts to precisely evaluate the risk factors; (iii) the relative importance among the risk factors is not taken into consideration, and hence, the results may not necessarily represent the true risk priorities; and etc. To overcome these drawbacks and improve the effectiveness of the traditional FMEA, we develop a fuzzy-FMEA approach for risk and failure mode analysis in offshore wind turbine systems. The information obtained from the experts is expressed using fuzzy linguistics terms, and a grey theory analysis is proposed to incorporate the relative importance of the risk factors into the determination of risk priority of failure modes. The proposed approach is applied to an offshore wind turbine system with sixteen mechanical, electrical and auxiliary assemblies, and the results are compared with the traditional FMEA.


2018 ◽  
Vol 13 (2) ◽  
pp. 205-220 ◽  
Author(s):  
Baoyu Liu ◽  
Yong Hu ◽  
Yong Deng

Failure mode and effects analysis (FMEA) is extensively applied to process potential faults in systems, designs, and products. Nevertheless, traditional FMEA, classical risk priority number (RPN), acquired by multiplying the ratings of occurrence, detection, and severity, risk assessment, is not effective to process the uncertainty in FMEA. Many methods have been proposed to solve the issue but deficiencies exist, such as huge computing quality and the mutual exclusivity of propositions. In fact, because of the subjectivity of experts, the boundary of two adjacent evaluation ratings is fuzzy so that the propositions are not mutually exclusive. To address the issues, in this paper, a new method to evaluate risk in FMEA based on D numbers and evidential downscaling method, named as D numbers downscaling method, is proposed. In the proposed method, D numbers based on the data are constructed to process uncertain information and aggregate the assessments of risk factors, for they permit propositions to be not exclusive mutually. Evidential downscaling method decreases the number of ratings from 10 to 3, and the frame of discernment from 2^{10} to 2^3 , which greatly reduce the computational complexity. Besides, a numerical example is illustrated to validate the high efficiency and feasibility of the proposed method.


2017 ◽  
Vol 6 (1) ◽  
pp. 29
Author(s):  
Ronald Sukwadi ◽  
Frederikus Wenehenubun ◽  
Tarsina Wati Wenehenubun

<p><em>This </em><em>study</em><em> </em><em>aims to</em><em> </em><em>identify and </em><em>analyze </em><em>the </em><em>risk factors </em><em>of</em><em> work accidents</em><em>. </em><em>Failure Mode and Effect Analysis (FMEA) and Fuzzy Logic </em><em>approach are applied</em><em>. </em><em>The information obtained from the workers is expressed using fuzzy linguistics terms, and a FMEA method is proposed to determine the risk priority of failure modes. </em><em>The results </em><em>indicate</em><em> that </em><em>injuries caused when struck by an object are the highest</em><em> risk factor </em><em>of work accident (</em><em>FRPN </em><em>=</em><em> 886</em><em>). Some work improvements are suggested to reduce or eliminate the work risks.</em><em></em></p><p><em>Keywords</em><em>: Risk factor</em><em>s</em><em>, work accident, FMEA, Fuzzy </em></p>


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Deyun Zhou ◽  
Yongchuan Tang ◽  
Wen Jiang

Due to the incomplete knowledge, how to handle the uncertain risk factors in failure mode and effects analysis (FMEA) is still an open issue. This paper proposes a new generalized evidential FMEA (GEFMEA) model to handle the uncertain risk factor, which may not be included in the conventional FMEA model. In GEFMEA, not only the conventional risk factors, the occurrence, severity, and detectability of the failure mode, but also the other incomplete risk factors are taken into consideration. In addition, the relative importance among all these risk factors is well addressed in the proposed method. GEFMEA is based on the generalized evidence theory, which is efficient in handling incomplete information in the open world. The efficiency and some merit of the proposed method are verified by the numerical example and a real case study on aircraft turbine rotor blades.


2012 ◽  
Vol 32 (S 01) ◽  
pp. S39-S42 ◽  
Author(s):  
S. Kocher ◽  
G. Asmelash ◽  
V. Makki ◽  
S. Müller ◽  
S. Krekeler ◽  
...  

SummaryThe retrospective observational study surveys the relationship between development of inhibitors in the treatment of haemophilia patients and risk factors such as changing FVIII products. A total of 119 patients were included in this study, 198 changes of FVIII products were evaluated. Results: During the observation period of 12 months none of the patients developed an inhibitor, which was temporally associated with a change of FVIII products. A frequent change of FVIII products didn’t lead to an increase in inhibitor risk. The change between plasmatic and recombinant preparations could not be confirmed as a risk factor. Furthermore, no correlation between treatment regimens, severity, patient age and comorbidities of the patients could be found.


2020 ◽  
Vol 32 (6) ◽  
pp. 347-355
Author(s):  
Mark Wahrenburg ◽  
Andreas Barth ◽  
Mohammad Izadi ◽  
Anas Rahhal

AbstractStructured products like collateralized loan obligations (CLOs) tend to offer significantly higher yield spreads than corporate bonds (CBs) with the same rating. At the same time, empirical evidence does not indicate that this higher yield is reduced by higher default losses of CLOs. The evidence thus suggests that CLOs offer higher expected returns compared to CB with similar credit risk. This study aims to analyze whether this return difference is captured by asset pricing factors. We show that market risk is the predominant risk factor for both CBs and CLOs. CLO investors, however, additionally demand a premium for their risk exposure towards systemic risk. This premium is inversely related to the rating class of the CLO.


2019 ◽  
Vol 17 (6) ◽  
pp. 591-594 ◽  
Author(s):  
John C. Stevenson ◽  
Sophia Tsiligiannis ◽  
Nick Panay

Cardiovascular disease, and particularly coronary heart disease (CHD), has a low incidence in premenopausal women. Loss of ovarian hormones during the perimenopause and menopause leads to a sharp increase in incidence. Although most CHD risk factors are common to both men and women, the menopause is a unique additional risk factor for women. Sex steroids have profound effects on many CHD risk factors. Their loss leads to adverse changes in lipids and lipoproteins, with increases being seen in low density lipoprotein (LDL) cholesterol and triglycerides, and decreases in high density lipoprotein (HDL) cholesterol. There is a reduction in insulin secretion and elimination, but increases in insulin resistance eventually result in increasing circulating insulin levels. There are changes in body fat distribution with accumulation in central and visceral fat which links to the other adverse metabolic changes. There is an increase in the incidence of hypertension and of type 2 diabetes mellitus, both major risk factors for CHD. Oestrogens have potent effects on blood vessels and their loss leads to dysfunction of the vascular endothelium. All of these changes result from loss of ovarian function contributing to the increased development of CHD. Risk factor assessment in perimenopausal women is recommended, thereby permitting the timely introduction of lifestyle, hormonal and therapeutic interventions to modify or reverse these adverse changes.


2002 ◽  
Vol 21 (1) ◽  
pp. 83-100 ◽  
Author(s):  
Jonathan I. Robison ◽  
Gregory Kline

In health education and promotion, “risk factors” for disease gathered from epidemiological research form the basis from which the majority of recommendations to individuals for lifestyle change are made. Unfortunately, many health practitioners are unaware that this type of research was never intended to be applied to individuals. The result is ongoing public confusion and anxiety concerning health recommendations and a loss of credibility for health professionals. This article: 1) briefly reviews the most commonly encountered limitations inherent in epidemiological research; 2) explores the problems and potential negative consequences of incorrectly applying epidemiological research in health education and promotion; and 3) makes recommendations to help health practitioners more skillfully interpret and incorporate into their work findings from epidemiological research.


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