TUV德國萊茵技術(shù)六西格碼培訓(xùn)BasicStatisticsforSPC課件

1、TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC2022/9/27TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatistiWhat is statistics?什么是統(tǒng)計Definition of statistics:統(tǒng)計的定義* Statistics are facts and figures.統(tǒng)計是事實和數(shù)據(jù)* Statistics consist of a set of methods and rules for organizing and interpreting obser

2、vations from populations and samples統(tǒng)計通過一系列方法和規(guī)則來組織、解釋來自總體和樣本的觀測值Populations and Samples總體和樣本* Population is the entire group or set of all possible events of interest in the particular study. 總體是被關(guān)注、研究的對象的全部* Sample is a subset of the population樣本是從總體中抽出的一部分ENTIRE POPULATION總體SAMPLE WITHIN(subset)樣

3、本A Statistic:統(tǒng)計值A(chǔ) numerical value that describes a sample用來描述樣本的數(shù)值TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCWhat is statistics?什么是統(tǒng)計DefiniTwo Types of Data統(tǒng)計獲得的兩種數(shù)據(jù)Attribute Data CategoriesYes, NoGo, No goMachine 1, Machine 2, Machine 3Pass/FailVariable Data Discrete (Count) DataMaintenance Equipment Fa

4、ilures, Number of ClogsNumber of customer returnsContinuous DataDecimal subdivisions are meaningfulTime, Pressure, Conveyor Speed 特性數(shù)據(jù)(定性)等級是非 通止 個體（如 1號機(jī)器, 2號機(jī)器, 3號機(jī)器)成敗變量數(shù)據(jù)（定量)間斷型數(shù)據(jù)（計數(shù)）如設(shè)備維修次數(shù)、阻塞次數(shù)等客戶退貨次數(shù)連續(xù)型數(shù)據(jù) (計量)可有小數(shù)點(diǎn)如時間、壓力、傳送速度等 TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCTwo Types of Data統(tǒng)計獲得的兩種數(shù)據(jù)At

5、tDescription of Continuous Data-Graphical計量型數(shù)據(jù)的描述-圖形HistogramHeight of 90 ladies# of ocurrenceHeight(inch) 數(shù)據(jù)分布圖在實際統(tǒng)計中， 統(tǒng)計結(jié)果是分段表示的，因此作出的分布圖為柱形圖。 在分析數(shù)據(jù)時，通常將它擬合成連續(xù)的曲線。TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCDescription of Continuous DataExamples of distributions 不同的分布Negative Skew負(fù)斜Positive Skew正斜Symmet

6、ric Distribution對稱分布Left-tailedRight-tailedTwo-tailedTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCExamples of distributions 不同的分Mean: Arithmetic average of a set of values 均值：算數(shù)平均值Reflects the influence of all values反映全部數(shù)據(jù)的影響Strongly Influenced by extreme values受特殊值干擾大Median: Reflects the 50% rank - the ce

7、nter number after a set of numbers has been sorted from low to high.中位數(shù)：反映 系列的一半將一組數(shù)據(jù)按大小順序排列，取中間的一個數(shù)據(jù)Does not include all values in calculation 計算中未包含全部數(shù)據(jù)Is “robust” to extreme outlier scores. 對特殊值的干擾有抵抗 The mean and median will be affected by the nature of the distribution of numbers. 均值和中值都受數(shù)據(jù)分布的影

8、響Mode: Most frequently occurring value in a data set. In a Pareto this is the largest bar on the chart. 眾數(shù)：數(shù)據(jù)中重復(fù)次數(shù)最多的值， 在柏拉圖上表現(xiàn)為最高的那條柱Description of Quantitative Data-Central Tendency計量型數(shù)據(jù)的描述-中心位置TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCMean: Arithmetic average of aRelationship: mean and median均值和中位數(shù)的比

9、較1101009080706050403020100500NormalFrequencyMean, Median807060504030201003002001000Neg SkewFrequencyMedianMean130120110100908070603002001000Pos SkewFrequencyMedianMeanTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCRelationship: mean and medianSample mean of a distribution樣本均值 Mean = Average= xi /Ni=1N = X1 +

10、 X2 +.XN NExamples:例Part weights零件重量: 8.47, 8.67, 9.34, 7.99 AVERAGE = 8.47 +8.67 + 9.34 + 7.99 = 8.62平均值4TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCSample mean of a distribution Dont Worry. That rope is one inch thick on the average.不要擔(dān)心。 繩子是平均一英寸粗TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCDont Worry. That r

11、ope is oneRange = maximum value - minimum value范圍=樣本內(nèi)最大值-最小值Variance= mean squared distance from the mean方差=數(shù)據(jù)與均值差距的平方之均值Standard deviation = is the square root of the variance and provides a measure of the standard distance from the mean.標(biāo)準(zhǔn)偏差=方差的開方Description of Quantitative Data-Dispersion or Spre

12、ad計量型數(shù)據(jù)的描述-離散度TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCRange = maximum value - minilDeviation（偏差） is the distance from the mean.是離開均值的距離lDeviation score（偏差值） = observation - true mean觀測值-均值lVariance 方差= mean or average of squared deviation scores偏差值的平方均值. is the symbol for variance方差的符號.lStandard Devia

13、tion標(biāo)準(zhǔn)偏差 = square root of variance方差的開方.is the symbol for the standard deviation.標(biāo)準(zhǔn)偏差的符號The Standard Deviation is a Measure of Variability標(biāo)準(zhǔn)偏差是對變異的描述m= PopulationMean 總體的均值iDeviation (distance from mean)偏差s2sStandard Deviation標(biāo)準(zhǔn)偏差TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPClDeviation（偏差） is the distances

14、= Sample Standard Deviation樣本標(biāo)準(zhǔn)偏差X= Sample Mean樣本均值= Population Mean總體均值Statistics Estimate Parameters= Population Standard Deviation總體標(biāo)準(zhǔn)偏差SamplePopulationSAMPLE樣本POPULATION總體Statistics or parameters?樣本統(tǒng)計值與總體參數(shù)？統(tǒng)計活動的實質(zhì)：用樣本統(tǒng)計值來估計總體參數(shù)，從而了解總體TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCs = Sample StandardX= S

15、amplPopulation vs. sample總體和樣本計算公式Population Mean總體均值Sample Mean樣本均值Population Standard Deviation總體標(biāo)準(zhǔn)偏差Sample Standard Deviation樣本標(biāo)準(zhǔn)偏差=x=xnii=1n =s=(X )n-1i2i=1nX TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCPopulation vs. sample總體和樣本計算公Example: Calculating “sigma”計算練習(xí)Using the form above, calculate the st

16、andard deviation for the numbers用上列的表計算以下5個數(shù)據(jù)的標(biāo)準(zhǔn)偏差：2， 1， 3， 5 ，4 X X-X (X-)2XTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCExample: Calculating “sigma”計算Exercise Solution計算結(jié)果: X X-X (X-)2XTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCExercise Solution計算結(jié)果: 數(shù)據(jù)的描述總覽分布的位置 LocationMean 均值Median 中值Mode 代表值Quantiles 分位數(shù)Q

17、1 四分之一處Q2 二分之一處Q3 四分之三處 P 機(jī)率位置離散度 SpreadRange 范圍Standard Deviation 標(biāo)準(zhǔn)偏差Variance 變差Stability Factor 穩(wěn)定因子Span 跨度Interquartile Range 內(nèi)分位寬度Sum of Squares 平方和Shape 形狀Histograms 直方圖Run Charts 運(yùn)行圖Time Plots 時序圖Scatter Plots 散點(diǎn)圖Box Plots 盒狀圖Block Chart 塊圖Normality Plot 正態(tài)性圖NumercialGraphicalTUV德國萊茵技術(shù)六西格碼培訓(xùn)資

18、料BasicStatisticsforSPC數(shù)據(jù)的描述總覽分布的位置 Location離散度 SpreaNormal Distribution正態(tài)分布Mean均值Bell-shape Symmetric Distribution倒鐘狀對稱分布fx(x)=12ps2e-(x-m)2/2s2TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCNormal Distribution正態(tài)分布Measured by Standard Deviation用標(biāo)準(zhǔn)偏差為尺度mean68.27 %15.865%15.865%TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatistics

19、forSPCMeasured by Standard DeviationMeasured by Standard Deviation用標(biāo)準(zhǔn)偏差為尺度mean95.45 %TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCMeasured by Standard Deviation68.2% 的數(shù)據(jù)落在1s 以內(nèi)95.4% 的數(shù)據(jù)落在2s 以內(nèi)99.7% 的數(shù)據(jù)落在3s 以內(nèi)99.99999975% 的數(shù)據(jù)落在6s 以內(nèi)Measured by Standard Deviation用標(biāo)準(zhǔn)偏差為尺度+4+5+6+1+2+3-2-1-4-3-6-5068.27%95.45%9

20、9.73%99.9937%99.999943%99.9999998%TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC68.2% 的數(shù)據(jù)落在1s 以內(nèi)Measured by S總體任意抽取4組樣品，每組3個樣品總體的參數(shù)樣品的統(tǒng)計值總體與樣品在統(tǒng)計上的關(guān)系 TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC總體任意抽取4組樣品，每組3個樣品總體的參數(shù)樣品的統(tǒng)計值總體樣品之間的統(tǒng)計分布TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC樣品之間的統(tǒng)計分布TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料Basi中心極限定理（Centra

21、l Limit Theorem）*條件:X1, X2, , Xn 是從總體中隨機(jī)抽取樣品的某特性的測量值，總體關(guān)于該特性的均值為 , 總體的標(biāo)準(zhǔn)偏差為 ,結(jié)論:該組樣品的均值 所屬分布（假定有多組這樣的樣品，多組的均值形成一個分布）的均值和標(biāo)準(zhǔn)偏差為:另外樣品大小 n 越大，組均值的分布越接近正態(tài)分布. nXXXnX+=.21使用正態(tài)分布來討論大多數(shù)問題的基礎(chǔ)TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC中心極限定理（Central Limit Theorem）*(a)正態(tài)型l(b)規(guī)則型(c)指數(shù)型(d)偶次方型總體分布形狀樣品大小 n = 2的均值分布 n =

22、 5n = 30不論其總體的分布如何，其樣品的均值的分布趨向正態(tài)分布實踐經(jīng)驗如果總體是正態(tài)分布, 樣品均值一定為正態(tài)分布，無論樣品大小如何如果總體的分布不夠?qū)ΨQ， 520的樣品大小即可最差的情形: 30的樣品大小可以應(yīng)付一切形狀的總體分布，無論總體的分布離正態(tài)分布相差多遠(yuǎn)TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC(a)正態(tài)型l(b)規(guī)則型(c)指數(shù)型(d)偶次方型總體分布二項分布與泊松分布計數(shù)型數(shù)據(jù)（合格與不合格）的分布遵從二項分布或泊松分布的規(guī)律：假定一批產(chǎn)品的不合格的幾率為p，從中隨機(jī)抽出一個容量為n的樣本，那么n件產(chǎn)品中不合格品數(shù)X是一個離散型的隨機(jī)變量

23、, 它服從二項分布（Binomial or Bernoulli)的規(guī)律。PX=r=Crnpr(1-p)n-r r=1, 2, ., n當(dāng)n 很大，不合格數(shù)nu很小時，不合格數(shù)Cnu的分布趨向于泊松分布(Poisson)： lc Pc= C-l C!當(dāng)n充分大（n50），nu不小于5時，二項分布和泊松分布都趨于正態(tài)分布。TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC二項分布與泊松分布TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasiVariation&Capability變差與過程能力TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCVariati

24、on變差與過程能力TUV德國萊茵技術(shù)六西格碼培Introduction to Variation什么是變差TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCIntroduction to VariationTUV德國160155150145165170175Will the ball always go the same distance? 球會總是落在同一點(diǎn)嗎？TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC160155150145165170175Will the There will always be variability pre

25、sent in any process變差存在于任何過程We can tolerate variability if 我們在下列條件下可以容忍變差The total variability of the Output is relatively small compared to the process specifications and the process is on target 與過程的工程規(guī)范相比較而言過程的變差很小,并且過程對中于目標(biāo)值The process is stable over time過程長時間穩(wěn)定LSLUSLNomUSLCost成本Traditional傳統(tǒng)觀念A(yù)

26、cceptable可接受LSLUSLNomCost成本New新觀念Can We Tolerate Variability?我們能容忍變差嗎?TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCThere will always be variabiliAs the standard deviation increases probability of defect increase標(biāo)準(zhǔn)偏差越大, 缺陷幾率越大1st distribution2nd distribution3rd distributionLower specUpper spec.Defects.Defec

27、ts& Distributions缺陷與分布形狀 p(d)缺陷幾率規(guī)范上限規(guī)范下限TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCAs the standard deviation incrProcess Capability過程能力TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCProcess CapabilityTUV德國萊茵技術(shù)六西格過程輸入的變差已知有兩種類型的過程變差:統(tǒng)計不受控: 與特殊原因有關(guān)統(tǒng)計受控: 與普通原因有關(guān)在研究過程表現(xiàn)時:特殊原因造成的變差往往表現(xiàn)為嚴(yán)重地偏離目標(biāo)值，或不隨機(jī)的平均值漂移普通原因造成的變差表現(xiàn)為

28、正態(tài)的隨機(jī)分布過程能力分析適用于 普通原因造成的變差TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC過程輸入的變差已知有兩種類型的過程變差:TUV德國萊茵技術(shù)六Process Capability Indicators過程能力指數(shù)Process Potential : Ratio of the specification width to 6 times工藝潛能 a measure of the process variation工程規(guī)范的寬度與六倍的過程標(biāo)準(zhǔn)偏差的比值Cp = USL-LSL 6sPPp = USL-LSL 6sTCp is used when t

29、he process is in a state of statistical control as defined by standard control charting methods. Cp用于統(tǒng)計穩(wěn)定的過程, 過程是否穩(wěn)定可由統(tǒng)計控制圖來確定Cp uses the pooled standard deviation. Cp使用分組匯合的標(biāo)準(zhǔn)偏差Pp is used when the process is NOT in a state of statistical control as defined by standard control charting methods. Pp u

30、ses the total standard deviation Pp用于統(tǒng)計不穩(wěn)定的過程, 它使用整體的標(biāo)準(zhǔn)偏差TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCProcess Capability IndicatorsPNot indicatingif centeredhere . . .不論中心在哪Or here . . .或這兒Or here . . .或這兒Indicators with variables data:變量數(shù)據(jù)的指示CpPpTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCNot indicatingOr here

31、. . .OTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatistisPsTPooled standard deviation 分組匯合標(biāo)準(zhǔn)偏差Taken over a relatively short time period.相對較短時間內(nèi)的數(shù)據(jù)Takes into account only the variation within a subset. 只計入小組內(nèi)的變差Contains only common causes of variation. 只包含普通原因的變差Total or Overall sta

32、ndard deviation 整體標(biāo)準(zhǔn)偏差Taken over sufficient subsets to show the variation due to all common and special causes of variation.足夠長時間內(nèi)的數(shù)據(jù)以展示普通原因的變差和特殊原因的變差Calculated from many samples that represent the shift anddrift that occurs in the population due to all causes of variation.從很多樣品中計算包含所有變差所帶來的總體漂移Poo

33、led Vs Overall Standard Deviation分組匯合標(biāo)準(zhǔn)偏差與整體標(biāo)準(zhǔn)偏差TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCsPsTPooled standard deviation Actual Process Performance : Ratio of the difference between the process average and the nearest specification to 3 times a measure of the process variation 實際過程的表現(xiàn):過程均值與最近的規(guī)范線的距離跟3倍的過

34、程標(biāo)準(zhǔn)偏差之比值Process Capability Indicators過程能力指數(shù)CPK = Min CPL, CPUCPL = X-LSL 3sPCPU = USL-X 3sPPPL = X-LSL 3sTPPU = USL-X 3sTPPK = Min PPL, PPUCpk is used when the process is in a state of statistical control as defined by standard control charting methods. Cp用于統(tǒng)計穩(wěn)定的過程, 過程是否穩(wěn)定可由統(tǒng)計控制圖來確定Cpk uses the pool

35、ed standard deviation. Cpk使用分組匯合的標(biāo)準(zhǔn)偏差Ppk is used when the process is NOT in a state of statistical control as defined by standard control charting methods. Pp uses the total standard deviation Ppk用于統(tǒng)計不穩(wěn)定的過程, 它使用整體的標(biāo)準(zhǔn)偏差TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCActual Process Performance : RIndicates Spre

36、ad & Distance分布寬度和距離的指示W(wǎng)idth & positionare indicated here指示了分布寬度和位置and here . . .and here . . .CpkPpkTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCIndicates Spread & Distance分布TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisti計算 Cp / Cpk Cp=LSL140USL260200Cp=LSL140USL260200Cp=LSL140USL2602

37、00Cp=LSL140USL260200215sst = 20sst = 20sst = 10sst = 10Cpk=Cpk=Cpk=Cpk=TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC計算 Cp / Cpk Cp=LSLUSL200Cp=LSLCpPPCPKPPKCapability能力Overall Std DevNot in Control長期整體標(biāo)準(zhǔn)偏差統(tǒng)計不受控Pooled Std DevIn Control短期分組匯合標(biāo)準(zhǔn)偏差統(tǒng)計受控Performance表現(xiàn)CP represents “entitlement”!Cp代表改進(jìn)的目標(biāo)Relates s

38、td. deviationto tolerance 考察標(biāo)準(zhǔn)偏差與公差寬度Relates mean & std. deviation to spec.考察均值/標(biāo)準(zhǔn)偏差和工程規(guī)范Short TermLong Term“Snapshot” Look照相“Video” Look 錄像TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCCpPPCapability能力Performance表Sample 3Sample 4Sample 5 s4 s3 s2 s1s5Total sT In a perfect state of control stotal = spPooled

39、 Standard Deviation分組匯合標(biāo)準(zhǔn)差“Average” Standard Deviation平均的標(biāo)準(zhǔn)偏差A(yù)ssuming equal subgroup sizeSample 2Sample 1 TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCSample 3Sample 4Sample 5s4 s3 MondaySubgroup 1子組1TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCMondaySubgroup 1子組1TUV德國萊茵技術(shù)六西TuesdayFromMondaySubgroup 2子組2TUV德國萊茵技術(shù)

40、六西格碼培訓(xùn)資料BasicStatisticsforSPCTuesdayFromSubgroup 2子組2TUV德國萊WednesdaySubgroup 3子組3FromMonday &TuesdayTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCWednesdaySubgroup 3子組3FromTUV德ThursdaySubgroup 4 子組4FromMon, Tues,WedTUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCThursdaySubgroup 4 子組4FromTUV德This distribution is made

41、 up of many smaller time periods.這一分布是由一段時間內(nèi)許多小分布組成Long Term DistributionSubgroups 1-4子組1-4TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCThis distribution is made up oMondayTuesdayWednesdayThursdayOVER TIME時間一長SHIFT HAPPENS漂移發(fā)生了TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCMondayTuesdayWednesdayThursdayWhich standa

42、rd deviation should we use?應(yīng)該選用哪種標(biāo)準(zhǔn)偏差?It depends on what we are trying to do取決于我們要作什么If we want to know the best our process is capable of,如果我們想知道過程的最佳狀態(tài)如何the process entitlement亦即過程的天賦能力use sst - the short term process capability使用短期標(biāo)準(zhǔn)差計算短期過程能力If we want to know what our customers see, 如果想了解客戶是怎么看的

43、our actual performance,我們的表現(xiàn)use slt - the long term process capability使用長期標(biāo)準(zhǔn)差計算長期過程能力If we want to know our opportunity for improvementUSE BOTH!如果我們想知道改進(jìn)的機(jī)會, 兩者都用TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPCWhich standard deviation shoul0The difference between sst and slt representsThe Area for Process Imp

44、rovement 短期標(biāo)準(zhǔn)差與長期標(biāo)準(zhǔn)差的差距代表改進(jìn)的空間The Focus of MAIC 改進(jìn)的關(guān)注點(diǎn)Another way of thinking about it另一中思考角度0TUV德國萊茵技術(shù)六西格碼培訓(xùn)資料BasicStatisticsforSPC0The difference between sst an YB 8207批號Y4092BY4092BY4092BY4092BY4092BY4092BY4092BY4092BY4092BY4095BY4095BY4095BY4095BY4095BY4095BY4095BY4095BY4095BY4095BY4095BMFI13.06

45、12.9512.3712.6013.1913.3312.7612.9712.7113.1912.2013.7012.0013.1612.2712.5712.7213.0213.0212.55批號Y4167BY4167BY4167BY4167BY4167BY4167BY4167BY4167BY4167BY4167BY4167BY4228BY4228BY4228BY4228BY4228BMFI12.8412.7413.0012.6012.6212.6413.0312.7413.1012.6012.6012.5612.8612.6014.0013.40批號Y4240BY4240BY4240BY4240BY4240BY4240BY4240BY4240BY4241BY4241BY4241BY4241BY4241BY4241BMFI12.5912.6011.9311.9712.9012.7512.3712.7013.0412.6012.9013.7012.4913.18Melt Flo