某著名汽车零部件公司15-da5doeslides020xx7dajama-ch-en-汽车(编辑修改稿)

某著名汽车零部件公司15-da5doeslides020xx7dajama-ch-en-汽车(编辑修改稿)内容摘要：

，因为我们看不到两个或更多因子同时改变时的效果。 这是说因子 A在因子 B处于高水平时和处于低水平时对输出的影响可能是不一样的。 OFAT Six Sigma Green Belt Training Design of Experiments (DoE) Read the case material provided and prepare the following as teams: 阅读所提供的案例材料并分组回答下面问题： • What was different about the designed experiment that Alex ran as pared to the OFAT experiment? Alex运行的经过设计的实验与 OFAT实验有什么不同。 • Is there now a pointer to an area where yields may be higher? 现在是否有指示出更高产出率的方向。 • What new inference space should Alex explore? Alex应该探求的新推论空间是什么。 Case Study – Yield Improvement Sections 4 amp。 5 案例分析 – 改善产出率之第四、五节 Six Sigma Green Belt Training Design of Experiments (DoE) • Full Factorial Designs (Factorial designs) test every possible bination of factors over the inference （因子实验）检验推论空间范围内的所有可能的组合 • These designs are of particular interest because they provide a great deal of information. 这些设计极其重要因为它们 提供了大量的信息。 • The amount of resources necessary to run full factorial designs can be exorbitant if the number of factors is large. Full factorials are generally run when the experimenter has a high degree of confidence that the factors in the study have an influence over the ，运行全因子实验所必需的资源数量是非常大的。 一般实验者在有高度的信心认为所研究的因子对输出有影响时才运行全因子实验。 Full Factorials 全因子实验 因子数量 (2水平 ) 运行次数 2 22 = 4 3 23 = 8 4 24 = 16 5 25 = 32 6 26 = 64 2n Factor columns (2n): 因子列 (2n): Exponent。 n = of factors to be tested 指数。 n = 因子数 Base。 2 = the of levels to be tested for each factor 基数。 2 = 每个因子的水平数 Six Sigma Green Belt Training Design of Experiments (DoE) DOE Design and Results: DOE设计和结果： Which Factors appear to be important? 哪一个参数看起来重要些 ? How should the important factors be set? 这些参数应该如何设定 ? Is there an Interaction between the variables? 因子之间是否存在交互作用 ? Full Factorial – Yield Improvement DOE 案例分析 – 改善产出率之 DOE Time Temp 时间 温度 Yield A B AB 产出率 70 () 145 () + 56 130 (+) 145 () 69 70 () 165 (+) 82 130 (+) 165 (+) + 58 Six Sigma Green Belt Training Design of Experiments (DoE)  The first consideration before applying any statistical analysis technique is whether the results of the DOE are of any practical 统计工具之前要考虑其结果是否有实用价值。  Did the response variable change? Did it change the desired amount?响应变量会随之变化吗 ? 变化量是否足够大 ? • If the response variable did not change substantially across the factor treatment binations, it may be that: 如果相应变量变化不够明显，可能是因为 : 1. Factor levels were not set far enough apart (didn’t go bold enough).因子水平设置不够大 (不够大胆 ) 2. The selected factors do not affect the response 影响 3. The measurement system is not  Practical 实用  Graphical 图示  Analytical 解析 Six Sigma Rules of Analysis: 六西格玛分析的规则  Practical实用 Six Sigma Green Belt Training Design of Experiments (DoE) • Another。