An interval probability-based FMEA model for risk assessment: A real-world case

Failure mode and effect analysis (FMEA) is an effective quality tool to eliminate the risks and enhance the stability and safety in the fields of manufacturing and service industry. Nevertheless, the conventional FMEA has been criticized for its drawbacks in the evaluation process of risk factors or the determination of risk priority number (RPN), which may lead to inaccurate evaluation results. Therefore, in this paper, we develop a novel FMEA method based on rough set and interval probability theories. The rough set theory is adopted to manipulate the subjectivity and uncertainty of experts' assessment and convert the evaluation values of risk factors into interval numbers. Meanwhile, the interval exponential RPN (ERPN) is used to replace the traditional RPN due to its superior properties, eg, solving the problems of duplicate numbers and discontinuity of RPN values. Furthermore, an interval probability comparison method is proposed to rank the risk priority of each failure mode for avoiding the information loss in the calculation process of RPN. Finally, a real case study is presented, and the comparison analysis among different FMEA methods is conducted to demonstrate the reliability and effectiveness of the proposed FMEA method.     

基于灰色关联分析激光熔覆Ni60A工艺参数优化

目的 针对激光熔覆Ni60A成形效率问题,研究工艺参数对单道熔覆效率和高宽比的影响规律,实现熔覆层工艺参数的预测与优化.方法 基于正交试验设计方法,采用信噪比对试验结果进行转换,并通过灰色关联分析多目标优化方法进行工艺参数优化.结果 最优工艺参数:激光功率为1900 W,扫描速度为8 mm/s,气流量为16 L/min...     

A linguistic risk prioritization approach for failure mode and effects analysis: A case study of medical product development

Failure mode and effects analysis (FMEA) is a widely used risk management technique for identifying the potential failures from a system, design, or process and determining the most serious ones for risk reduction. Nonetheless, the traditional FMEA method has been criticized for having many deficiencies. Further, in the real world, FMEA team members are usually bounded rationality, and thus, their psychological behaviors should be considered. In response, this study presents a novel risk priority model for FMEA by using interval two‐tuple linguistic variables and an integrated multicriteria decision‐making (MCDM) method. The interval two‐tuple linguistic variables are used to capture FMEA team members' diverse assessments on the risk of failure modes and the weights of risk factors. An integrated MCDM method based on regret theory and TODIM (an acronym in Portuguese for interactive MCDM) is developed to prioritize failure modes taking experts' psychological behaviors into account. Finally, an illustrative example regarding medical product development is included to verify the feasibility and effectiveness of the proposed FMEA. By comparing with other existing methods, the proposed linguistic FMEA approach is shown to be more advantageous in ranking failure modes under the uncertain and complex environment.     

A rough TOPSIS Approach for Failure Mode and Effects Analysis in Uncertain Environments

This study aims at improving the effectiveness of failure mode and effect analysis (FMEA) technique. FMEA is a widely used technique for identifying and eliminating known or potential failures from system, design, and process. However, in conventional FMEA, risk factors of Severity (S), Occurrence (O), and Detection difficulty (D) are simply multiplied to obtain a crisp risk priority number without considering the subjectivity and vagueness in decision makers’ judgments. Besides, the weights for risk factors S, O, and D are also ignored. As a result, the effectiveness and accuracy of the FMEA are affected. To solve this problem, a novel FMEA approach for obtaining a more rational rank of failure modes is proposed. Basically, two stages of evaluation process are described: the determination of risk factors’ weights and ranking the risk for the failure modes. A rough group ‘Technique for Order Performance by Similarity to Ideal Solution’ (TOPSIS) method is used to evaluate the risk of failure mode. The novel approach integrates the strength of rough set theory in handling vagueness and the merit of TOPSIS in modeling multi‐criteria decision making. Finally, an application in steam valve system is provided to demonstrate the potential of the methodology under vague and subjective environment. Copyright © 2013 John Wiley & Sons, Ltd.     

基于FMEA和FTA的老年人汽车人机界面交互设计研究

目的 提升老年人汽车界面满意度,设计适合老年人使用的汽车界面.方法 提出基于失效模式与效应分析(FMEA)、故障树分析(FTA)的研究方法,首先成立会议小组进行SHERPA分析,绘制汽车界面层次任务分析图;随后运用FMEA找出汽车界面中的潜在失效模式,计算风险优先数值;接着选取风险优先数值高的失效模式,运用FTA寻找其发生的原因,对其以图形化表示;再对故障树进行定性定量分析,计算故障树的最小切集和失效事件发生概率,找到失效发生的核心因素;最后对失效事件进行改良并对改良后的结果进行验证.结论 以老年人汽车界面为例进行研究,该方法可以有效发现老年人操作汽车界面发生错误的原因,不仅可以帮助设计师找到改良的重点,还可以使老年人获得良好的驾驶体验.     

Nitrogen Doped γ‐Graphyne: A Novel Anode for High‐Capacity Rechargeable Alkali‐Ion Batteries

High energy density is the major demand for next‐generation rechargeable batteries, while the intrinsic low alkali metal adsorption of traditional carbon–based electrode remains the main challenge. Here, the mechanochemical route is proposed to prepare nitrogen doped γ‐graphyne (NGY) and its high capacity is demonstrated in lithium (LIBs)/sodium (SIBs) ion batteries. The sample delivers large reversible Li (1037 mAh g^?1) and Na (570.4 mAh g^?1) storage capacities at 100 mA g^?1 and presents excellent rate capabilities (526 mAh g^?1 for LIBs and 180.2 mAh g^?1 for SIBs) at 5 A g^?1. The superior Li/Na storage mechanisms of NGY are revealed by its 2D morphology evolution, quantitative kinetics, and theoretical calculations. The effects on the diffusion barriers (E_b) and adsorption energies (E_ad) of Li/Na atoms in NGY are also studied and imine‐N is demonstrated to be the ideal doping format to enhance the Li/Na storage performance. Besides, the Li/Na adsorption routes in NGY are optimized according to the experimental and the first‐principles calculation results. This work provides a facile way to fabricate high capacity electrodes in LIBs/SIBs, which is also instructive for the design of other heteroatomic doped electrodes.     

Improved FMEA based on IVF and fuzzy VIKOR method: A case study of workpiece box system of CNC gear milling machine

Failure mode and effect analysis (FMEA) is a tool used to define, identify, and prevent known or unknown potential risks. An improved FMEA based on interval triangular fuzzy numbers (IVF) and fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is proposed in this study to solve problems of expression and processing of uncertain information, weights of risk factors, and ranking of failure modes in traditional FMEA. Linguistic variables are used to evaluate failure modes level and relative importance of risk factors and are expressed via interval-valued triangular fuzzy number. Determining the subjective weights of risk factors using fuzzy AHP, calculating the objective weights of risk factors using the extended VIKOR method, and obtaining the comprehensive weights of risk factors via ICWGT are proposed for solving the weight problem of risk factors. Finally, the fuzzy VIKOR method is used to rank risk priority of failure modes. The proposed method is used to evaluate workpiece box system of CNC gear milling machine and the results are compared with the findings of other methods to verify effectiveness and rationality of the proposed method.     

Failure mode and effect analysis using the hesitant intuitionistic fuzzy hybrid GRP approach with ordered comprehensive weights

Failure mode and effect analysis (FMEA), a multidisciplinary reliability analysis tool based on team evaluations, has been widely used in various industries. There are three critical issues in FMEA: the conversion of linguistic evaluations, the weights of risk factors, and the ranking mechanism of failure modes. Scholars have used various fuzzy theories and multi-attribute decision-making (MADM) methods to improve traditional FMEA, but there are still deficiencies. In this paper, the hesitant intuitionistic fuzzy set (HIFS), a concept that combines the intuitionistic fuzzy set (IFS) and the hesitant fuzzy set (HFS), is introduced into FMEA to convert linguistic evaluations. Some operators based on HIFS are proposed to process the converted data. Among them, a hesitant intuitionistic fuzzy comprehensive weighted Hamming distance (HIFCWHD) operator is proposed to compute the ordered comprehensive weight, effectively weakening the effect of extreme scores on results. The gray relational projection (GRP) method is adopted to determine the risk priority order of the failure modes. Finally, we give an illustrative case to demonstrate the effectiveness of the proposed FMEA method.     

A Novel Approach to Realize Si‐Based Porous Wire‐In‐Tube Nanostructures for High‐Performance Lithium‐Ion Batteries

Hollow inorganic nanostructures have drawn great attention due to their fascinating features, such as large surface area, high loading capacity, and high permeability. The formation, characterization, and application of partially and entirely hollow structure by applying a Si‐based reactive ion deposition and etching method on silicon nanowire as a template are reported. This fabrication technique is extended to a stainless steel substrate to be used as the binder‐free anode for high capacity and high rate lithium‐ion batteries. The electrochemical analyses exhibit that in addition to the high initial discharge capacity of 4125 mAh g^?1 at a rate of C/16, the best performing electrode shows discharge/charge capacity of as high as 3302.14/2832.1 mAh g^?1, respectively, with an excellent charge capacity retention of 96.7% over 100 cycles at a rate density of 1 C. Even at a rate of 12 C, the as‐designed structure is still able to deliver an impressive 1553 mAh g^?1, which probably is attributed to fast lithium diffusion in its hollow part and high porosity of Si and alumina layer. It is proved that the change in hollowness ratio significantly affects capacity retention and average coulombic efficiency of the lithium‐ion cells.