针对传统故障模式和影响分析(failure mode and effect analysis,FMEA)方法存在评价使用精确数量化造成专家风险评估信息的丢失、忽略风险指标之间的相对重要性以及由于专家有限理性导致的评价固有的随机性等问题,利用区间值直觉模糊集和云模型构建了一种改进的FMEA风险评估方法.首先,引入区间值直觉模糊集(IVIFS)来描述专家评价信息的复杂性和不确定性,通过运用区间值直觉模糊熵,计算专家权重和风险因子的权重;其次,采用云模型的方法,通过比较各支持云模型和反对云模型与正、负理想云模型的正、负相似度,获得故障模式评价值的综合相似度,通过对综合相似度大小排序得到各故障模式风险排序;最后,以自动扶梯的梯级、踏板和胶带风险评估为例进行分析,验证该评估方法的实用性和可行性.
FMEA risk assessment method based on interval valued intuitionistic fuzzy sets and cloud model
Aiming at the problems of traditional failure mode and effect analysis(FMEA)methods,such as the loss of expert risk assessment information caused by precise quantification of evaluation,the neglect of relative importance between risk indicators,and the inherent randomness of evaluation caused by expert bounded rationality,an improved FMEA risk assessment method was constructed using interval valued in-tuitionistic fuzzy sets and cloud models.Firstly,interval valued intuitionistic fuzzy sets(IVIFS)were intro-duced to describe the complexity and uncertainty of expert evaluation information.By using interval intu-itionistic fuzzy entropy,the weights of experts and risk factors were calculated.Secondly,using the cloud model approach,the comprehensive similarity of fault mode evaluation values was obtained by comparing the positive and negative similarities between various supporting and opposing cloud models and positive and negative ideal cloud models.The risk ranking of each fault mode was obtained by sorting the size of the comprehensive similarity.Finally,taking the risk assessment of escalator steps,pedals,and tape as an exam-ple for analysis,the practicality and feasibility of this evaluation method were verified.
万方数据
维普
