多粒度概率语言环境下基于PROMETHEE的改进FMEA方法

Improved FMEA method based on PROMETHEE in multi-granular probabilistic linguistic environment

针对传统故障模式和影响分析(FMEA)方法中存在关于故障模式评估、风险因子权重和风险优先级排序等方面的固有缺陷,提出了一种多粒度概率语言环境下基于偏好顺序结构评估法(PROMETHEE)的改进FMEA方法。该方法运用多粒度概率语言术语集(PLTS)刻画了专家评估信息的多样性和不确定性,并基于二元语义转换函数为引入工具的语言计算模型统一各专家多粒度风险评估信息,运用最优最劣法(BWM)和熵权法相结合的综合赋权法确定风险因子权重,将PROMETHEE拓展到概率语言环境中用于确定故障模式风险优先序。最后,运用托盘交换架故障风险评估案例来验证该方法的适用性和有效性,并进一步通过敏感度与对比分析以显示该方法的优越性。

With respect to some inherent drawbacks regarding failure mode evaluations,risk factor weights and risk priority ranking in traditional failure mode and effect analysis(FMEA)method,an improved FMEA method based on preference ranking organization method for enrichment evaluations(PROMETHEE)in multi-granular probabilistic linguistic environment was proposed.The multi-granular probabilistic linguistic term sets(PLTS)were used to characterize the diversity and uncertainty of experts’assessment information,and a new linguistic computational model was developed based on the 2-tuple linguistic transformation formulas to unify the multi-granular risk assessment information provided by FMEA team members.Best-worst method(BWM)and the entropy weighting method were adopted to determine subjective and objective combined weights of risk factors.The PROMETHEEE was extended to probabilistic linguistic environment to determine the risk ranking of failure modes.Finally,an empirical case concerning the failure risk evaluation of tray automatic exchange device was presented to demonstrate the practicality and effectiveness of the proposed method,and sensitivity analysis and comparison study were also performed to show its merits.