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.     

基于FMEA的老年人电子产品交互设计研究

目的设计适合老年人使用的电子产品。方法提出基于失效模式与效应分析的方法,成立FMEA专家小组进行讨论;对现有老年人电子产品进行潜在失效模式分析,计算风险优先数值(RPN);针对需要改进的失效模式进行合理的设计改良;针对改良后的产品进行设计评价。结论将失效模式与效应分析的方法应用于老年人电子产品设计,可以发现设计源头问题,尽早采取改进方案,从而使老年人在使用电子产品时,拥有一个良好的交互体验。     

基于改进FMEA的适老化智能药盒交互设计研究

目的 基于适老化智能药盒交互失效模式的数据,对智能药盒的交互模式进行优化设计,提升交互体验,有效降低交互差错率。方法 首先,成立改进FMEA专家小组进行系统性人因错误减少和预测方法分析（Systematic Human Error Reduction and Prediction Approach, SHERPA）;其次,构建智能药盒交互失误预防模型,然后对适老化智能药盒交互设计进行改进失效模式与效应分析（FailureModeand Effects Analysis, FMEA）;最后,针对需要改进的失效模式对智能药盒进行设计优化。结果 实验结果显示“实证对象”存在诸多交互失效模式,对相应交互失效模式进行优化,可有效提升老年人操作智能药盒的交互体验。结论 运用改进FMEA的方法,可以具体量化适老化智能药盒交互失效模式数据,对应失效模式数据的智能药盒交互优化设计,是可行有效的,能够有效降低老年人的用药风险,此方法可为产品交互设计研究提供新的方法路径。     

基于FTA的老年人APP交互设计

目的提升老年人对APP的满意度,帮助老年人更好地接受和使用APP。方法提出基于故障树分析(FTA)的老年人APP交互设计方法。首先通过焦点小组确定导致错误发生的原因并建立故障树,对错误发生的原因进行合理分类;随后对故障树进行定性定量分析,计算故障树的最小切集和错误发生的概率,找到导致头号事件发生的核心因素;接着进行重要度分析,计算构造重要度,根据构造重要度值对引起错误发生的基本事件进行排序,为设计改良提供理论上的优先顺序;最后以老年人医疗APP为研究案例进行设计改良,并对改良后的结果进行错误率验证。结论该方法可以有效地发现老年人操作APP时出现障碍的原因,不仅可以帮助设计师找到较为合理的改良方案,而且还可以使老年人获得良好的交互体验。     

集成鱼骨分析与进化法则的产品失效预测及问题求解

 基于传统FMEA在失效问题分析与解决方面的不足,提出了一种集成鱼骨图、FMEA和进化法则的创新设计方法．利用鱼骨图层次化分析辅助FMEA全面挖掘可能发生的失效模式,按照FMEA的规范表达分析失效模式并确定风险优先指数RPN,然后运用进化法则针对失效问题进行有效的解决,提高了解决问题的效率．最后通过铁路减振的示例验证了该集成方法的可行性．     

失效模式与效应分析的作业方式

失效模式与效应分析(FMEA)是一套科学而完善的分析方式,是一项事前预防性的分析工作,在设计与制造确定之前用来探讨失效的因果关系。     

模糊集理论与灰色关联理论的FMEA方法

在对传统FMEA研究的基础上,提出了基于模糊集理论和灰色关联理论的FMEA方法.结合模糊集理论建立评价失效模式的模糊语言术语集和模糊数,对各种失效模式进行评价,利用灰色关联理论计算各种失效模式的关联度,通过排序来确定失效模式的风险顺序.该方法克服了传统FMEA的缺陷,提高了FMEA应用的准确性和可靠性.     

基于FMEA的网购服务失误预防模型

从顾客的感知角度出发,拟采用失效模式与效应分析(FMEA)方法进行网购服务失误的预防。将容忍区域的概念引入到FMEA中,通过将服务质量感知差距模型与FMEA结合,建立网购服务失误预防模型。同时,对传统的风险优先数进行了改进,提出了适用于网购服务环境下的改进指数型风险优先数。改进后的风险优先数考虑了容忍区域,可以更加精确地描述潜在的服务失效模式,迅速辨别失效模式所处的区域。实证研究结果进一步表明了提出的网购服务失误预防模型的有效性。     

基于结合分析的老年人APP用户体验优化设计研究

目的 优化老年人APP的用户体验。方法 提出老年人APP用户体验的优化设计方法。首先采用文献研究和焦点小组方法,制定APP的设计模式,并构建样本;其次构建用户体验的评价体系,对样本进行偏好评估;最后,通过建立设计模式与用户体验之间的数学模型,得到老年人APP的产品最优组合。结论 以老年人医疗APP为例进行优化设计,为设计师提供设计指南。     

基于FMEA的化学分析原始记录设计与应用

对材料理化性能检测实验室化学分析项目的 实验过程及原始记录设计进行分析与讨论,根据潜在失效模式及影响分析FMEA(failure mode and effect analysis)原理,将FMEA方法运用到实验过程的风险分析及管理中,将发现和补救机制融合到原始记录的设计中,对实验过程的质量控制进行闭环管理,有效减少操作...     

An alternative evaluation of FMEA: Fuzzy ART algorithm

Failure Mode and Effects Analysis (FMEA) is a technique used in the manufacturing industry to improve production quality and productivity. It is a method that evaluates possible failures in the system, design, process or service. It aims to continuously improve and decrease these kinds of failure modes. Adaptive Resonance Theory (ART) is one of the learning algorithms without consultants, which are developed for clustering problems in artificial neural networks. In the FMEA method, every failure mode in the system is analyzed according to severity, occurrence and detection. Then, risk priority number (RPN) is acquired by multiplication of these three factors and the necessary failures are improved with respect to the determined threshold value. In addition, there exist many shortcomings of the traditional FMEA method, which affect its efficiency and thus limit its realization. To respond to these difficulties, this study introduces the method named Fuzzy Adaptive Resonance Theory (Fuzzy ART), one of the ART networks, to evaluate RPN in FMEA. Copyright © 2008 John Wiley & Sons, Ltd.     

A quantitative method for Failure Mode and Effects Analysis

Failure Mode and Effects Analysis (FMEA) is commonly used for designing maintenance routines by analysing potential failures, predicting their effect and facilitating preventive action. It is used to make decisions on operational and capital expenditure. The literature has reported that despite its popularity, the FMEA method lacks transparency, repeatability and the ability to continuously improve maintenance routines. In this paper an enhancement to the FMEA method is proposed, which enables the probability of asset failure to be expressed as a function of explanatory variables, such as age, operating conditions or process measurements. The probability of failure and an estimate of the total costs can be used to determine maintenance routines. The procedure facilitates continuous improvement as the dataset builds up. The proposed method is illustrated through two datasets on failures. The first was based on an operating company exploiting a major gas field in the Netherlands. The second was retrieved from the public record and covers degradation occurrences of nuclear power plants in the United States.     

FMEA方法及8D模式在挤出 复合机生产中的应用

针对挤出复合机生产过程中电线未压到端口的缺陷实例,简要介绍了FMFA方法 (潜在的失效模式及效应分析)及8D模式原理,提出了挤出复合机生产企业如何应用FMFA方法及8D模式、建立失效模式及效应分析、有效采取过程控制方法及步骤解决质量问题与缺陷的相关对策和建议。     

Project Risk Management Using the Project Risk FMEA

Abstract:

Identifying and mitigating project risks are crucial steps in managing successful projects. This article proposes the extension of the Failure Mode and Effects Analysis (FMEA) format to quantify and analyze project risks. The new technique is labeled the project risk FMEA (RFMEA). The RFMEA is a modification of the well-known process, product, and service FMEA technique. In order to use the FMEA format for projects, the detection value of the standard FMEA is modified slightly for use in the project environment. The new approach is illustrated in a case study from the electronics industry. By adding the detection value to the risk quantification process, another measure beyond the typical risk score is made available to the project team. The benefits of the RFMEA include an increased focus on the most imminent risks, prioritizing risk contingency planning, improved team participation in the risk management process, and development of improved risk controls.     

Applying UGF Concept to Enhance the Assessment Capability of FMEA

The purpose of this paper is to propose a modified version of Failure Mode and Effects Analysis (FMEA) to alleviate its drawbacks. FMEA is an important tool in risk evaluation and finding the priority of potential failure modes for corrective actions. In the proposed method, the Universal Generating Function (UGF) approach has been used to improve the assessment capability of the conventional Risk Priority Number (RPN) in ranking. The new method is named as URPN. It generates the most number of unique values in comparison with the previous methods and considers relative importance for the parameters while it is easy to compute. More unique numbers help to avoid from having the same priority level for different failure modes which represent various risk levels. A case study has been employed to demonstrate that the URPN not only can improve the shortcomings but also is able to provide accurate values for risk assessment. Copyright © 2015 John Wiley & Sons, Ltd.     

Research on Reliability of Automatic Capping Device for Nuclear Power Plant

Automatic capping device is a complex and non-standard equipment, its reliability directly impacts the safety operation of Solid Waste Treatment System （TES） in nuclear power plant. In order to improve the reliability automatic capping device, the equipment function and machine structure are analyzed. And Failure Mode and Effects Analysis （FMEA） method is applied to systematically analyze all possible failure modes and their reliability. Through establishing the FMEA worksheet, all failure causes, failure effects and their severity are analyzed comprehensively. Base on these analyzing resuhs, it is easy to find out the product function design defects and weak links. Finally, through putting forward design prevention and improvement measures in design, the mission reliability of automatic capping device is improved, and most serious failure mode occurrence is avoided efficiently. Thus the safety operation of TES has been guaranteed in technology.     

Using a failure modes, effects and diagnostic analysis (FMEDA) to measure diagnostic coverage in programmable electronic systems

One of the key issues in the quantitative evaluation of programmable electronic systems is the diagnostic capability of the equipment. This is measured by a parameter called the Coverage Factor, C. This factor can vary widely. The range of possible values is often the subject of great debate. Within limits, the diagnostic coverage factor can be calculated by knowing which component failure modes are detected by diagnostics. An extension of the Failure Modes and Effects Analysis (FMEA) can be used to show this information. This extension, called a Failure Modes, Effects and Diagnostic Analysis can serve as a useful design verification tool as well as a means to provide more precise input to reliability and safety modeling.     

Contribution to development of risk analysis methods by application of artificial intelligence techniques

During the life cycle of technical systems, precise and detail failure risk analysis gives suitable input elements for taking appropriate actions, which allows reducing of unwanted uncertainty and occurrences. Traditional method for risk analysis, which is applied for many years, especially in analysis of functionality of technical systems, is Failure Mode and Effects Analysis (FMEA) method. However, in many cases, this method shows weaknesses related to the inconsistency, which is a result of insecure subjectivity during the determination of values for parameters that gives Risk Priority Number (RPN), as well as other weaknesses. This paper shows contribution to the development of failure risk analysis based on FMEA method. Contribution of the development of risk analysis methods is given through modification of traditional FMEA method by integration of artificial intelligence techniques, in this case, by integration of fuzzy logic and by including a few principles based on special classification of recognized failures. Thus, it is minimized effect of methodological inconsistency and some of other identified weaknesses of traditional FMEA method. FMEA method is improved, which provides more precise failure risk evaluation and thus better prediction and minimizing of unwanted occurrences (failures of elements, subsystems, components, etc., of technical systems). It was proved by comparative analysis of applied traditional FMEA method as well as modified FMEA method, hereinafter called “intelligent” FMEA method (IFMEA) on system of tires for city busses.