基于模糊FMEA方法的高校云数字档案系统安全风险评价方法

高校档案管理向着数字化、在线化、智能化和共享化发展,在提高档案管理效率和技术服务能力的同时也带来了新的风险问题,但是目前高校云数字档案系统缺少定量风险评估方法。采用组合语言评价信息作为专家评价表述方式,基于三角模糊数AHP方法确定各个评价参数的权重信息,提出了一种新的模糊FMEA方法用于计算高校云数字档案系统的整体风险和风险等级,并给出案例验证了此方法的正确性和可行性。

Prediction of subsidence risk by FMEA using artificial neural network and fuzzy inference system

Construction of metro tunnels in dense and crowded urban areas is faced with many risks, such as sub- sidence. The purpose of this paper was the prediction of subsidence risk by failure mode and effect anal- ysis （FMEA） and fuzzy inference system （FIS）. Fuzzy theory will be able to model uncertainties. Fuzzy FMEA provides a tool that can work in a better way with vague concepts and without sufficient informa- tion than conventional FMEA. In this paper, S and D are obtained from fuzzy rules and 0 is obtained from artificial neural network （ANN）. FMEA is performed by developing a fuzzy risk priority number （FRPN）. The FRPN for two stations in Tehran No.4 subway line is 3.1 and 5.5, respectively. To investigate the suit- ability of this approach, the predictions by FMEA have been compared with actual data. The results show that this method can be useful in the prediction of subsidence risk in urban tunnels.

Failure Mode and Effects Analysis （FMEA） by Fuzzy Data Envelop Analysis （Fuzzy-DEA）

Failure mode and effects analysis （FMEA） offers a quick and easy way for identifying ranking-order for all failure modes in a system or a product. In FMEA the ranking methods is so called risk priority number （RPN）, which is a mathematical product of severity （S）, occurrence （0）, and detection （D）. One of major disadvantages of this ranking-order is that the failure mode with different combination of SODs may generate same RPN resulting in difficult decision-making. Another shortfall of FMEA is lacking of discerning contribution factors, which lead to insufficient information about scaling of improving effort. Through data envelopment analysis （DEA） technique and its extension, the proposed approach evolves the current rankings for failure modes by exclusively investigating SOD in lieu of RPN and to furnish with improving sca.les for SOD. The purpose of present study is to propose a state-of-the-art new approach to enhance assessment capabilities of failure mode and effects analysis （FMEA）. The paper proposes a state-of-the-art new approach, robust, structured and useful in practice, for failure analysis.

Analysis of Potential Failure Modes in an Assembly Line by Fuzzy Expert Systems

The failure modes and effects analysis （FMEA） is widely applied in manufacturing industries in various phases of the product life cycle to evaluate the system, its design and processes for failures that can occur. The FMEA team often demonstrates different opinions and these different types of opinions are very difficult to incorporate into the FMEA by the traditional risk priority number model. In this paper, for each of the Occurrence, Severity and Detectivity parameters a fuzzy set is defined and the opinion of each FMEA team members is considered. These opinions are considered simultaneously with weights that are given to each individual based on their skills and experience levels. In addition, the opinion of the costumer is considered for each of the FMEA parameters. Then, the Risk Priority Numbers （RPN） is calculated using a Multi Input Single Output （MISO） fuzzy expert system. The proposed model is applied for prioritizing the failures of Peugeot 206 Engine assembly line in IKCo （Iran Khodro Company）.

产品概念设计结构优化的裁剪组件确定方法

在现有优化概念方案中,裁剪方法的确定组件环节存在欠缺,提出以理想度优化为目标的裁剪组件确定方法。根据概念方案确定产品完成主要功能的流程,采用可拓表达构建功能事元。通过拓展分析进行潜在问题分析,将关键潜在问题的相关组件作为待裁剪组件。通过模糊故障模式影响分析(Failure Mode and Effects Analysis,FMEA)计算负面功能值,基于CRITIC权重法确定影响因素的权重值,计算待裁剪组件的优先权,提出产品概念设计结构优化的裁剪流程。对温室穴盘苗移栽机进行优化,验证此方法的可行性。研究结果表明:改进的裁剪方法可在概念设计阶段优化产品结构,提高方案理想度。