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KPOVs analytical memod based on improved weighted dynamic pareto chart

机译：基于改进的加权动态Pareto图表的KPOV分析备忘录

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The core of Lean Six Sigma quality improvement is to identify key process output variables (KPOV) of products or services according to the “critical to quality” (CTQ), then find out the key process input variables(KPIV), so that the quality improvement focus can be ascertained. To solve the problems of traditional Pareto chart in identifying the KPOV that do not consider the fuzzy attribute of quality and unequal opportunities of improvement for KPOVs, the improved weighted dynamic Pareto chart is presented. Based on determining the CTQ, after process analysis, the membership degree analytical method of fuzzy quality is applied to dynamically analysis the relevant data of the process output variables (POVs), and the combination weighting method based on entropy theory is utilized to reasonably assess the improving opportunities of process output variables. Finally, in an instance application, the improved weighted dynamic Pareto chart is used to dynamically determine the key process output variables of the repair cycle. The method provides an effective approach for the organization to determine the direction of Lean Six Sigma improve project.
机译：精益六西格码质量改进的核心是根据“对质量至关重要”（CTQ）识别产品或服务的关键过程输出变量（KPOV），然后找出关键过程输入变量（KPIV），从而确保质量可以确定改进重点。为了解决传统的帕累托图在识别KPOV时不考虑质量模糊属性和KPOV改进机会不均等问题，提出了改进的加权动态帕累托图。在确定CTQ的基础上，经过过程分析，运用模糊质量的隶属度分析方法对过程输出变量（POV）的相关数据进行动态分析，并利用基于熵理论的组合加权法对过程质量进行合理评估。改善过程输出变量的机会。最后，在实例应用程序中，使用改进的加权动态帕累托图来动态确定维修周期的关键过程输出变量。该方法为组织确定精益六西格玛改进项目的方向提供了有效的方法。

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