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【正文】 tness the significant event. The event may simply never happen, or happen when no one is around to observe 可以目擊到顯著的事件。 B, we can also calculate the effect of the interaction between factors A amp。 ? The cube plot is a geometrical representation of the data. 立體圖是用幾何圖形來表達數(shù)據(jù) ? The shape is determined by the number of factors (2 factors are a square, 3 factors a cube), the number of levels and the distance between (2因子時是正方形 , 3因子時是立方體 )、 水平數(shù)和水平間距決定 Cube Plot 58 69 56 82 Temp B Time A + + ? Graphical圖示 時間 溫度 Time Temp 產(chǎn)出率 A B AB Yield 70 () 145 () + 56 130 (+) 145 () 69 70 () 165 (+) 82 130 (+) 165 (+) + 58 Six Sigma Green Belt Training Design of Experiments (DoE) To pute the impact of a factor in a DOE, (called the “effect” of the variable), calculate the difference between the average of the results at each level of the factor: 在 DOE中因子影響的計算， (叫做因子的“效果” )，計算每一水平結(jié)果的平均值之間的差異。查看因子的趨勢。 2 = 每個因子的水平數(shù) Six Sigma Green Belt Training Design of Experiments (DoE) DOE Design and Results: DOE設(shè)計和結(jié)果： Which Factors appear to be important? 哪一個參數(shù)看起來重要些 ? How should the important factors be set? 這些參數(shù)應(yīng)該如何設(shè)定 ? Is there an Interaction between the variables? 因子之間是否存在交互作用 ? Full Factorial – Yield Improvement DOE 案例分析 – 改善產(chǎn)出率之 DOE Time Temp 時間 溫度 Yield A B AB 產(chǎn)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 統(tǒng)計工具之前要考慮其結(jié)果是否有實用價值。 n = 因子數(shù) Base。 Full Factorials 全因子實驗 因子數(shù)量 (2水平 ) 運行次數(shù) 2 22 = 4 3 23 = 8 4 24 = 16 5 25 = 32 6 26 = 64 2n Factor columns (2n): 因子列 (2n): Exponent。 ? 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 ，運行全因子實驗所必需的資源數(shù)量是非常大的。 OFAT Six Sigma Green Belt Training Design of Experiments (DoE) Read the case material provided and prepare the following as teams: 閱讀所提供的案例材料并分組回答下面問題： ? What was different about the designed experiment that Alex ran as pared to the OFAT experiment? Alex運行的經(jīng)過設(shè)計的實驗與 OFAT實驗有什么不同？ ? Is there now a pointer to an area where yields may be higher? 現(xiàn)在是否有指示出更高產(chǎn)出率的方向？ ? What new inference space should Alex explore? Alex應(yīng)該探求的新推論空間是什么？ Case Study – Yield Improvement Sections 4 amp。 ? OFAT experiments do not allow interactions to show themselves, since we cannot see the effect of two or more variables changing simultaneous
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