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【正文】 ? DOE is a rich topic – see your Black Belt for more 豐富，找你們的黑帶了解更多的信息。這個(gè)事件可能永遠(yuǎn)不會(huì)發(fā)生，或者發(fā)生時(shí)卻沒人在旁邊看到。 Effect = (Average of all runs at + level) (Average of all runs at level) 效果 = (+ 水平所有運(yùn)行的平均值 ) ( 水平所有運(yùn)行的平均值 ) For this problem, A(+) A() A(+)=(69+58)/2 = A()=(56+82)/2 = Therefore the main effect of A 因此 A的主效果 = 69 = ? Graphical圖示 When factor ?A? changes from high to low the yield increases by A從“＋”改變成“－”時(shí)，產(chǎn)出率提高了 B Temp 165 (+) 145 () 130 (+) 58 69 70 () 82 56 A Time A B30701651857 27 68 08 48 8YM a i n E f f e c t s P l o t ( d a t a m e a n s ) f o r YSix Sigma Green Belt Training Design of Experiments (DoE) To determine the interaction effect use the +, column to group the data just like before. 如前方法，用 +、 對(duì)數(shù)據(jù)分組計(jì)算交互作用的效果 In this case: 此例中： ? In addition to the main effects for factors A amp。 ? Did the response variable change? Did it change the desired amount?響應(yīng)變量會(huì)隨之變化嗎 ? 變化量是否足夠大 ? ? If the response variable did not change substantially across the factor treatment binations, it may be that: 如果相應(yīng)變量變化不夠明顯，可能是因?yàn)?: 1. Factor levels were not set far enough apart (didn’t go bold enough).因子水平設(shè)置不夠大 (不夠大膽 ) 2. The selected factors do not affect the response 影響 3. The measurement system is not ? Practical 實(shí)用 ? Graphical 圖示 ? Analytical 解析 Six Sigma Rules of Analysis: 六西格瑪分析的規(guī)則 ? Practical實(shí)用 Six Sigma Green Belt Training Design of Experiments (DoE) ? Another practical technique is to sort the treatments based on the response to look for trends in the factors. 另外一種實(shí)用技術(shù)是把響應(yīng)變量排序，看因子是否呈現(xiàn)規(guī)律 ? If factor A had a large impact on yield, how would the ranking appear? What about factor B? 如果因子 A對(duì)產(chǎn)出率有很大影響，它的順序會(huì)呈怎樣的規(guī)律？ B因子呢 ? ? Based on this analysis, what preliminary actions would you remend right now?基于這些分析，你當(dāng)前會(huì)建議采取哪些行動(dòng)？ 時(shí)間 溫度 Time Temp 產(chǎn)出率 A B AB Yield 70 () 145 () + 56 130 (+) 165 (+) + 58 130 (+) 145 () 69 70 () 165 (+) 82 ? Practical實(shí)用 Sort results by output and look for trends in one or more of the factors 按輸出排序的結(jié)果。 n = of factors to be tested 指數(shù) 。 5 案例分析 – 改善產(chǎn)出率之第四、五節(jié) Six Sigma Green Belt Training Design of Experiments (DoE) ? Full Factorial Designs (Factorial designs) test every possible bination of factors over the inference （因子實(shí)驗(yàn)）檢驗(yàn)推論空間范圍內(nèi)的所有可能的組合 ? These designs are of particular interest because they provide a great deal of information. 這些設(shè)計(jì)極其重要因?yàn)樗鼈?提供了大量的信息 。 找到根源性因子（影響響應(yīng)的因子）的時(shí)間太長(zhǎng)。 But are they? 果真如此嗎？ ? Is it reasonable to assume that one can hold all variables constant while manipulating one? 假定在改變一個(gè)因子時(shí)能保持所有其它的因子不變，可能嗎？ Experience tells us this is virtually impossible. 實(shí)踐證明這決不可能。 Experimentation the manipul
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