scholarly journals A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2145
Author(s):  
James J. H. Liou ◽  
Perry C. Y. Liu ◽  
Huai-Wei Lo

Reducing the potential risks in the manufacturing process to improve the reliability of the switched-mode power supply (SMPS) is a critical issue for the users’ safety. This paper proposes a novel failure mode and effects analysis (FMEA) model based on hybrid multiple criteria decision-making (MCDM), which adopts neutrosophic set theory into the proposed model. A developed neutrosophic Best Worst method (NBWM) is used to evaluate the weights of risk factors and determine their importance. Secondly, the neutrosophic Weight Aggregated Sum Product Assessments (NWASPAS) method is utilized to calculate the Risk Priority Number (RPN) of the failure modes. The proposed model improves the shortcomings of traditional FMEA and improves the practical applicability and effectiveness of the Best Worst method (BWM) and Weight Aggregated Sum Product Assessments (WASPAS) methods. In addition, this study uses neutrosophic logic to reflect the true judgments of experts in the assessment, which considers authenticity, deviation, and uncertainty to obtain more reliable information. Finally, an empirical case study from an SMPS company headquartered in Taiwan demonstrates the effectiveness and robustness of the proposed model. In addition, by comparing with two other FMEA models, the results show that the proposed model can more clearly reflect the true and effective risks in the assessment. The results can effectively help power supply manufacturers to assess risk factors and determine key failure modes.

2020 ◽  
Vol 33 (5) ◽  
pp. 881-904 ◽  
Author(s):  
Reza Fattahi ◽  
Reza Tavakkoli-Moghaddam ◽  
Mohammad Khalilzadeh ◽  
Nasser Shahsavari-Pour ◽  
Roya Soltani

PurposeRisk assessment is a very important step toward managing risks in various organizations and industries. One of the most extensively applied risk assessment techniques is failure mode and effects analysis (FMEA). In this paper, a novel fuzzy multiple-criteria decision-making (MCDM)-based FMEA model is proposed for assessing the risks of different failure modes more accurately.Design/methodology/approachIn this model, the weight of each failure mode is considered instead of risk priority number (RPN). Additionally, three criteria of time, cost and profit are added to the three previous risk factors of occurrence (O), severity (S) and detection (D). Furthermore, the weights of the mentioned criteria and the priority weights of the decision-makers calculated by modified fuzzy AHP and fuzzy weighted MULTIMOORA methods, respectively, are considered in the proposed model. A new ranking method of fuzzy numbers is also utilized in both proposed fuzzy MCDM methods.FindingsTo show the capability and usefulness of the suggested fuzzy MCDM-based FMEA model, Kerman Steel Industries Factory is considered as a case study. Moreover, a sensitivity analysis is conducted for validating the achieved results. Findings indicate that the proposed model is a beneficial and applicable tool for risk assessment.Originality/valueTo the best of authors’ knowledge, no research has considered the weights of failure modes, the weights of risk factors and the priority weights of decision-makers simultaneously in the FMEA method.


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.


2021 ◽  
Author(s):  
Chuanxi Jin ◽  
Yan Ran ◽  
Genbao Zhang

Abstract In order to enhance quality and reliability of mechanical and electrical products, the methods of taking corresponding corrective measures to eliminate or alleviate product failure in advance have been widely concerned. Failure mode and effects analysis (FMEA) is a typical prevention reliability analysis method. However, there are some drawbacks in traditional FMEA method. To overcome these drawbacks, we propose a hybrid risk evaluation method, which combines picture fuzzy sets (PFSs), the PF-linear programming model (PF-LPM) method and the PF-weighted aggregated sum product assessment (PF-WASPAS) method. We adopt PFSs to evaluate risks of products. In order to overcome drawback of the traditional distance between PFSs, some new distance measures between PFSs based on the Dice similarity and the Jaccard similarity are proposed by us. The PF-LPM method which considers the subjective weights of risk factors and calculates synthetical deviation with the Dice similarity-based distance is utilized to calculate the weights of risk factors. Moreover, the PFWA operator and the PFWG operator are used by us to fuse experts’ evaluation information. Then, the PF-WASPAS method is utilized to rank failure modes. Finally, an illustrative example with respect to pallet exchange rack is introduced, and the rationality, effectiveness and applicability of the proposed method are verified by a discussion and comparison.


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>


2021 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Afshin Farhanchi ◽  
Zohreh Rahimi ◽  
Ehsan Saqhei ◽  
Farshad Farhani Deljoo

Background: Healthcare statistics, issued by various international organizations, show that medical errors in health centers impose high costs on patients and hospitals and increase the rates of morbidity and mortality around the world. Due to the potential risks of cardiovascular diseases, the occurrence of any errors can potentially endanger the patients’ lives and incur costs on them, as well as hospitals. On the other hand, anesthesia is one of the priorities for risk management in clinical care. Objectives: This study aimed to identify, classify, and evaluate anesthesia failures in open heart surgeries, using the healthcare failure mode and effects analysis (HFMEA) technique. Methods: The anesthesia process in open heart surgery was reviewed using the HFMEA technique, and four processes, 25 sub-processes, 95 activities, and 204 risks were extracted. The causes of failure were also identified, and four failure modes were determined as the most important failures, based on the qualitative and quantitative methods; finally, some solutions were proposed. Changes in the level of healthcare workers’ knowledge and competence, computer use and timing, and the amount of administered medications were identified as the potential risk factors and errors. Results: The inadequate awareness and knowledge of healthcare workers, non-use of computers, prescription errors, technique errors, and timing and amount of medication administration were identified as the errors and risk factors. Based on the present findings, another expert needs to evaluate the design, feasibility, and prioritization of techniques, including continuing medical education for anesthesia professionals and experts, statutory documentation, and control of the individuals’ activities. Conclusions: Based on the present findings, establishing a risk management committee seems essential to identify errors and improve the design and plan of different techniques so as to execute, monitor, control, and review errors in a cycle of continuous improvement.


2010 ◽  
Vol 38 (3) ◽  
pp. 228-244 ◽  
Author(s):  
Nenggen Ding ◽  
Saied Taheri

Abstract Easy-to-use tire models for vehicle dynamics have been persistently studied for such applications as control design and model-based on-line estimation. This paper proposes a modified combined-slip tire model based on Dugoff tire. The proposed model takes emphasis on less time consumption for calculation and uses a minimum set of parameters to express tire forces. Modification of Dugoff tire model is made on two aspects: one is taking different tire/road friction coefficients for different magnitudes of slip and the other is employing the concept of friction ellipse. The proposed model is evaluated by comparison with the LuGre tire model. Although there are some discrepancies between the two models, the proposed combined-slip model is generally acceptable due to its simplicity and easiness to use. Extracting parameters from the coefficients of a Magic Formula tire model based on measured tire data, the proposed model is further evaluated by conducting a double lane change maneuver, and simulation results show that the trajectory using the proposed tire model is closer to that using the Magic Formula tire model than Dugoff tire model.


Author(s):  
Cha-Ming Shen ◽  
Tsan-Cheng Chuang ◽  
Jie-Fei Chang ◽  
Jin-Hong Chou

Abstract This paper presents a novel deductive methodology, which is accomplished by applying difference analysis to nano-probing technique. In order to prove the novel methodology, the specimens with 90nm process and soft failures were chosen for the experiment. The objective is to overcome the difficulty in detecting non-visual, erratic, and complex failure modes. And the original idea of this deductive method is based on the complete measurement of electrical characteristic by nano-probing and difference analysis. The capability to distinguish erratic and invisible defect was proven, even when the compound and complicated failure mode resulted in a puzzling characteristic.


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