基于DMAIC方法论的微控制器产品终测良品率改善

发布时间：2018-04-02 20:09

本文选题：六西格玛　切入点：DMAIC　出处：《天津大学》2015年硕士论文

【摘要】：本文的研究背景是飞思卡尔半导体从摩托罗拉剥离出来之后,急需寻找一种可以在终测阶段改善良品率的系统性方法。本论文的主要内容是首先从六西格玛在飞思卡尔半导体本企业内部的推行开始,引出终测良品率改善方面的探讨。然后围绕微控制器产品在飞思卡尔天津工厂运用DMAIC方法改善终测良品率方面的特征和必要性方面论述。DMAIC分为定义阶段、测量阶段、分析阶段、改善阶段和控制阶段。其中定义阶段主要定义了团队组织架构,研究范围以及收益评估指标。并运用流程图,柏拉图和二八法则等识别出了影响良品率改善的重要因素。接着在测量阶段,主要评估了当前的制程能力水平即长期过程能力指数和当前所研究产品的百万分之缺陷率。从而为下一阶段提供了可供水平对比的基准。分析阶段中主要运用了鱼骨图,潜在失效模式及结果分析,独立性检验,正态性检验,方差假设检验,均值的假设检验和非参数检验。此外,还运用了方差分析进行了多变异源分析。改善阶段主要运用了全因子实验设计法进行了因子的优化,并用比例假设检验进行了验证,重新进行了潜在失效模式及结果分析,确定了执行计划。控制阶段中重新进行了过程能力分析,运用了控制图进行监控并把改善文件化以便巩固改善成果,以及和初始目标对比以确定改善收益。最后六西格玛方法针对终测良品率改善所面临的困境,从大数据角度进行构想建议,以促进终测良品率改善手段能够更加发展。
[Abstract]:The background of this paper is that after Freescale semiconductor is stripped from Motorola, it is urgent to find a systematic method to improve the yield of good products in the final phase.The main content of this thesis is to begin with the implementation of six Sigma in Freescale Semiconductor Enterprise and to discuss the improvement of final quality rate.Based on the characteristics and necessity of using DMAIC method to improve the final product rate in Freescale Tianjin factory, the paper discusses that DMAIC can be divided into three stages: definition stage, measurement stage, analysis stage, improvement stage and control stage.The definition stage mainly defines the organizational structure of the team, the scope of research and income evaluation indicators.Using flowchart, Plato and the law of 28 to identify the important factors affecting the improvement of the rate of good products.Then, in the measurement stage, the current process capability level, that is, the long-term process capability index (LPI), and the percentage of defects in the current products are evaluated.This provides a baseline for the next stage of the level comparison.In the analysis stage, fish bone map, potential failure mode and result analysis, independence test, normality test, variance hypothesis test, mean hypothesis test and nonparametric test are mainly used.In addition, the analysis of variance was used to analyze the multiple sources of variation.In the improvement stage, the factors are optimized by using the full-factor experimental design method, and verified by the proportion hypothesis test. The potential failure mode and the result analysis are redone, and the execution plan is determined.Process capability analysis was reperformed during the control phase, control charts were used to monitor and document improvements to consolidate improvements, and improvements were compared to initial targets to determine improvement benefits.Finally, six Sigma method is proposed from big data's point of view in order to promote the improvement of the final good product rate in view of the difficulties faced by the improvement of the final good product rate.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F273.2;F416.63

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