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Click to edit Master title style,Click to edit Master text styles,Second level,Third level,Fourth level,*,Chapter 3.2,Measurement Systems Analysis,测量系统分析,1,测量是科学的基础,“I often say that when you measure what you are speaking about and express it in numbers, you know something about it.”,LORD KELVIN,The Science of Measurement,2,Effects of Measurement Error,Averages,Variability,m,m,m,total,product,meas.system,=,+,Measurement System Bias,Measurement System Variability,Accuracy,Precision,s,2,total,=,s,2,product,+,s,2,meas system,3,测量误差,平均值,变差,m,m,m,总,产品,测量系统,=,+,测量系统的偏差,测量系统的变差,准确度,精确度,s,2,total,=,s,2,产品,+,s,2,测量系统,4,Sources of Measurement Variation,M,e,a,s,u,r,e,m,e,n,t,V,a,r,i,a,t,i,o,n,H,u,m,i,d,i,t,y,C,l,e,a,n,l,i,n,e,s,s,V,i,b,r,a,t,i,o,n,L,i,n,e,V,o,l,t,a,g,e,V,a,r,i,a,t,ion,T,e,m,p,e,r,a,t,u,r,e,F,l,u,c,t,u,a,tion,O,p,e,r,a,t,o,r,T,e,c,h,n,i,q,u,e,S,t,a,n,d,a,r,d,P,r,o,c,e,d,u,r,e,s,S,u,f,f,i,c,i,e,n,t,W,o,r,k,T,i,m,e,M,a,i,n,t,e,n,a,n,c,e,S,t,a,n,d,a,r,d,C,a,l,i,b,r,a,t,i,o,n,F,r,e,q,u,e,n,cy,O,p,e,r,a,t,o,r,T,r,a,i,n,i,n,g,E,a,s,e,o,f,D,a,t,a,E,n,t,r,y,A,l,g,o,r,i,t,h,m,I,n,s,t,a,b,i,lty,E,l,e,c,t,r,i,c,a,l,I,n,s,t,a,b,i,l,ity,W,e,a,r,Mechanical instability,Gage,Environment,Work Methods,5,测量误差的原因,M,e,a,s,u,r,e,m,e,n,t,V,a,r,i,a,t,i,o,n,H,u,m,i,d,i,t,y,C,l,e,a,n,l,i,n,e,s,s,V,i,b,r,a,t,i,o,n,L,i,n,e,V,o,l,t,a,g,e,V,a,r,i,a,t,ion,T,e,m,p,e,r,a,t,u,r,e,F,l,u,c,t,u,a,tion,O,p,e,r,a,t,o,r,T,e,c,h,n,i,q,u,e,S,t,a,n,d,a,r,d,P,r,o,c,e,d,u,r,e,s,S,u,f,f,i,c,i,e,n,t,W,o,r,k,T,i,m,e,M,a,i,n,t,e,n,a,n,c,e,S,t,a,n,d,a,r,d,C,a,l,i,b,r,a,t,i,o,n,F,r,e,q,u,e,n,cy,O,p,e,r,a,t,o,r,T,r,a,i,n,i,n,g,E,a,s,e,o,f,D,a,t,a,E,n,t,r,y,电性能不稳定,磨损,机械不稳定性,量具,环境,测量方法,计算不稳定,取得数据的难易,操作员培训,校准频率,量具维护标准,足够的工作时间,标准操作规程,操作员技术,湿度,清洁程度,震动,线电压波动,温度波动,6,看到的不一定真实,7,Possible Sources of Process Variation,Long-term,Process Variation,Short-term,Process Variation,Variation,w/i sample,Actual Process Variation,Stability,Linearity,Repeatability,Accuracy,Variation due,to gage,Variation due,to operators,Measurement Variation,Observed Process Variation,We will look at “repeatability” and “reproducibility” as these are the primary contributors to measurement error.,Reproducibility,8,过程变差剖析,长期,过程变差,短期,抽样产生的变差,实际过程变差,稳定性,线性,重复性,准确度,量具变差,操作员造成的变差,测量误差,过程变差观测值,“,重复性” 和 “再现性” 是测量误差的主要来源,再现性,过程变差,9,Accuracy,Accuracy Does the,average,of the measurements deviate from the true value?,True value:,Theoretically correct value,NIST standards,Bias,Distance between average value of all measurements and true value,Amount gage is consistently off target,Systematic error or offset,10,准确度(,Accuracy),准确度(,Accuracy) ,测量的平均值是否与真值吻合?,真值(,True Value):,理论上正确的值,国际度量衡标准,偏倚（,Bias),测量值的均值与真值的距离,测量系统持续地偏离目标,系统错误,11,BIAS ,Is the difference between the observed average of the measurement and the reference value. The reference-value is the value that serves as an agreed-upon reference. The reference value can be determined by averaging several measurements with a higher level (e.g., metrology lab) of measuring equipment.,Observed,Average,Value,Reference,Value,BIAS Definition,12,BIAS ,测量结果的平均值与参考值的差异,. 参考值（,reference-value）,是一个预先认定的参考标准. 该标准可用更高一级测量系统测量的平均值来确定(例如：高一级计量室),观测平均值,参考值,偏倚,BIAS,13,X1=0.75mmX6=0.8mm,X2=0.75mmX7=0.75mm,X3=0.8mmX8=0.75mm,X4=0.8mmX9=0.75mm,X5=0.65mmX10=0.7mm,One Part Measured Ten Times by One Appraiser,What else do you need to determine BIAS?,The reference Value determined by the layout inspection equipment (ensure this equipment went through a Gage R&R) is 0.80mm. The process variation for the part is 0.70mm.,= 0.75,Bias = 0.75-0.8= -0.05,% Bias=1000.05/0.70=7.1%,This means 7.1% of the process variation is BIAS,BIAS EXAMPLE:,14,X1=0.75mmX6=0.8mm,X2=0.75mmX7=0.75mm,X3=0.8mmX8=0.75mm,X4=0.8mmX9=0.75mm,X5=0.65mmX10=0.7mm,同一操作者对同一工件测量10次,如果参考标准是 0.80,mm.,过程变差为0.70,mm,= 0.75,Bias = 0.75-0.8= -0.05,% Bias=1000.05/0.70=7.1%,表明 7.1% 的过程变差是偏倚,BIAS,偏倚,BIAS,实例:,15,Precision,Total variation in the measurement system,Measure of natural variation of repeated measurements,Terms: Random Error, Spread, Test/Retest error,Repeatability and Reproducibility,s,s,s,MS,G,O,2,2,2,=,+,16,测量系统总变差,通过重复测量的方法测量到的过程自然变差,代表名词：重复性（,Repeatability）,和再现性（,Reproducibility）,s,s,s,MS,G,O,2,2,2,=,+,精确度（,Precision),17,Precision: Repeatability,The inherent variability of the measurement system,Variation in measurements obtained with a gage when used several times by one operator while measuring a characteristic on one part.,Estimated by the pooled standard deviation of the distribution of repeated measurements,Repeatability is less than the total variation of the measurement system,18,测量系统内在的变异性,基于重复测量的数据，用分组后组内的标准偏差来估算,小于测量系统的总变差,重复性,指同,一,人使用同一测量工具对同一对象（产品）的同一特性进行多次测量中产生的变差，用于估计短期的变差,Master Value,精确度：重复性,19,Precision: Reproducibility,Operator variability of the measurement system,Variation in the average of the measurements made by different operators using the same gage when measuring a characteristic on one part,Estimated by the standard deviation of the difference in averages, based on measurements taken by different operators,Must be adjusted for gage variation,Reproducibility is less than the total variation of the measurement system,20,精确度：再现性,测量系统中操作员产生的变异,基于不同操作者的测量数据，按操作员分组，通过组平均值的差来估。,应扣除量具的因素（组内变差）,比测量系统总变差小,Inspector A,Master Value,Inspector B,Inspector C,Inspector A,Inspector B,Inspector C,再现性,指不同的人在对同种特性进行测量时产生的变差,21,Linearity,Difference in the accuracy values of a gage through the expected operating range of the gage,Good Linearity,Bad Linearity,22,线性（,Linearity）,量具在不同测量范围的准确度和精确度的变化，当测量范围较宽时尤为要关注,好的线性,差的线性,23,Stability,The distribution of measurements remains constant and predictable over time for both mean and standard deviation,Total variation in the measurements obtained with a gage, on the same master or master parts, when measuring a single characteristic over an extended time period.,Evaluated using a trend chart or multiple measurement analysis studies over time,Time-1,Time-2,time,Magnitude,Stability,24,在一段时间内，测量结果的分布无论是均值还是标准偏差都保持不变和可预测的,通过较长时间内，用被监视的量具对相同的标准或 标准件的同一特性进行测量的总变异来监视,可用时间走势图进行分析,稳定性（,Stability）,时间-1,时间-2,时间,稳定性,量值,25,Discrimination,The technological ability of the measurement system to adequately differentiate between values of a measured parameter.,Ruler,Caliper,Micrometer,.28,.279,.2794,.28,.282,.2822,.28,.282,.2819,.28,.279,.2791,26,测量系统的分辨率（,discrimination）,要求不低于过程变差或允许偏差（,tolerance）,的十分之一,零件之间的差异必须大于最小测量刻度,极差控制图可显示分辨率是否足够,看控制限内有多少个数据阶级,不同数据等级的计算为,零件的标准偏差/ 总的量具偏差* 1.41.,直尺,卡尺,千分尺,.28,.279,.2794,.28,.282,.2822,.28,.282,.2819,.28,.279,.2791,27,Generally two or three operators,Generally 10 units to measure,Each unit is measured 2-3 times by each operator,Gage R&R study,Determine if reproducibility is an issue. If it is, select the number of operators to participate.,Operators selected should normally use the measurement system.,Select samples that,represent the entire operating range,.,Gage must have graduations that allow at least one-tenth of the expected process variation.,Insure defined,gaging,procedures are followed.,Measurements should be made in random order.,Study must be observed by someone who recognizes the importance of conducting a reliable study.,28,计量型数据的,GR&R,研究,均值-极差（,X-R）,法是确定测量系统的重复性和再现性的数学方法，步骤如下：,1 选择三个测量人（,A, B,C）,和10个测量样品。,测量人应有代表性，代表经常从事此项测量工作的,QC,人员或生产线人员,10个样品应在过程中随机抽取，可代表整个过程的变差，否则会严重影响研究结果。,2 校准量具,3 测量，让三个测量人对10个样品的某项特性进行测试，每个样品每人测量,三次，将数据填入表中。试验时遵循以下原则：,盲测原则1：对10个样品编号，每个人测完第一轮后，由其他人对这10个样品进行随机的重新编号后再测，避免主观偏向。,盲测原则2：三个人之间都互相不知道其他人的测量结果。,4 计算,29,计算,A,测的所有样品,的总平均值,X,A,。,同样方法计算,R,B, X,B, R,C,Xc,对每个样品由三个人所测得的,9个测试值求平均值，,计算这些均值的极差,Rp,计算,A,对每个样品三次,测试结果的极差，,然后计算10 个样品,的极差的均值,R,A,30,测量系统分析,R=(R,A,+R,B,+R,C,)/3,X,DIFF,=MaxX,A,X,B,X,C,-MinX,A,X,B,X,C,重复性-设备变差,EV=R,K,1,再现性-测验人变差,AV= (X,DIFF,K,2,),2,-(EV,2,/nr),过程变差,PV=R,P,K,3,R&R= (EV,2,+AV,2,),总变差,TV= (R&R,2,+PV,2,),%EV=EV/TV,%AV=AV/TV,%R&R=R&R/TV,%PV=PV/TV,P/T=R&R/Tolerance,n=,样品个数,r=,每个人对每个样品的试验次数,r,K,1,2,3,4.45,3.05,K,2,2,3,3.65,2.70,测试人数,n,K,3,7,8,9,10,1.82,1.74,1.67,1.62,K,1,=5.15/d,2,*AV,计算中，如根号下出现负值，,AV,取值0,31,EV= Equipment Variation (Repeatability),仪器变差(重复性),AV= Appraiser Variation (Reproducibility),测量人变差(再现性),R&R= Repeatability & Reproducibility,重复性与再现性,PV= Part Variation,零件变差,TV= Total Variation of R&R and PV,总变差,K1-Trial, K2-Operator, & K3-Part Constants,GR&R,研究中的名词,32,卡尺的,R&R,研究,Excel,运算,33,R&R,对过程能力计算的影响,70%,60%,50%,40%,30%,10%,R&R Effect on Capability,34,Guidelines,% R&R,Results,5%No issues,10%Gage is OK,10% 30%Maybe acceptable based upon importanceof application, and cost factor,Over 30%Gage system needs improvement/correctiveaction,Variable Gage R&R,35,% R&R,Results, 30%测量系统需要改进,Gage R&R,判断原则,36,StdDev Study Var %Study Var %Tolerance,Source (SD) (5.15*SD) (%SV) (SV/Toler),Total Gage R&R 1.85E-02 0.095449 18.87 19.09,Repeatability 1.42E-02 0.073006 14.44 14.60,Reproducibility 1.19E-02 0.061486 12.16 12.30,Part-to-Part 9.64E-02 0.496646 98.20 99.33,Total Variation 9.82E-02 0.505735 100.00 101.15,Number of distinct categories = 7,Minitab,计算,GR&R,Xbar-R,均值极差法,注：使用同组数据,Discrim,98.2,18.9,=,s,s,p,ms,=,=,*,*,.,2,2,7.3,MinitabStatQuality ToolsGage StudyGage R&R Study (Crossed),在,Method of Analysis,中选择,Xbar and R,37,Minitab,计算,GR&R,图解数据,38,%Contribution,Source VarComp (of VarComp),Total Gage R&R 0.000459 4.53,Repeatability 0.000231 2.28,Reproducibility 0.000228 2.25,Operator 0.000117 1.16,Operator*Part No 0.000111 1.09,Part-To-Part 0.009670 95.47,Total Variation 0.010129 100.00,StdDev Study Var %Study Var %Tolerance,Source (SD) (5.15*SD) (%SV) (SV/Toler),Total Gage R&R 0.021430 0.110366 21.29 22.07,Repeatability 0.015202 0.078292 15.11 15.66,Reproducibility 0.015105 0.077789 15.01 15.56,Operator 0.010834 0.055793 10.76 11.16,Operator*Part No 0.010525 0.054205 10.46 10.84,Part-To-Part 0.098336 0.506430 97.71 101.29,Total Variation 0.100644 0.518317 100.00 103.66,Number of Distinct Categories = 6,Minitab,计算,GR&R-ANOVA,法,在,Method of Analysis,中选择,ANOVA,39,Measurement Variation Vs. Tolerance,Precision to Tolerance Ratio,Addresses what percent of the,Tolerance,is taken up by measurement error.,Best case: 10% Acceptable: 30%,Includes both repeatability and reproducibility,Operator x Unit x Trial experiment,P/T Ratios are required by certain customers,Usually expressed as percent,Tolerance = USL - LSL,Note,: 5.15 standard deviations accounts for 99% of MS variation. The use of 5.15 is an industry standard.,40,Measurement Variation Vs. Process (Analytical),Percent Repeatability & Reproducibility (%R&R),Addresses what percent of the,Total Variation,is taken up by measurement error.,Best case: 10% Acceptable: 30%,Includes both repeatability and reproducibility,Operator x Unit x Trial experiment,Again, the stability in the repeated measurements as well as the degree of discrimination could affect the validity of the calculation.,%R&R is required by certain customers,Usually expressed as percent,%,&,R,R,MS,Total,=,s,s,100,MS,s,41,P/T,与 %,R&R,将测量系统的变差与产品容差比较是最常用的方法:,P/T,可以表达与产品规范比较时的好坏程度.,产品规范的制订有时会太紧，有时又太松。,一般来说，当测量系统只是用来检验生产线样品是否合格时，,P/T,是很有效的。因为这时候，即使过程能力(,Cpk),不足，,P/T,也可以给你足够的信心来判断产品的好坏,测量系统变差与过程变差的比较（%,R&R）,更适合于研究过程的能力与过程改进。,P,T,Tolerance（,容差）,测量系统,/,.,*,=,5,15,s,Tolerance = USL - LSL,%,&,R,R,测量系统,总过程变差,=,s,s,100,42,%R&R = 20%,%R&R = 50%,过程实际的变差,%R&R = 100%,产品的容差,LSL,USL,测量系统变差,P/T = 20%,P/T = 50%,P/T = 100%,43,%R&R = 25%,%R&R = 50%,过程实际变差,%R&R = 100%,产品容差（,Tolerance）,LSL,USL,测量系统变差,P/T = 50%,P/T = 100%,P/T = 200%,44,%R&R = 20%,%R&R = 40%,%R&R = 100%,产品容差（,Tolerance）,LSL,USL,测量系统变差,P/T = 10%,P/T = 20%,P/T = 50%,过程实际变差,45,平均范围 = = (2+1+1+2+1)/5 = 7/5 = 1.4,量具误差 = 5.15 * /,d =5.15 / 1.19 * = 4.33 * = 4.33 * 1.4 = 6.1,% Gage R&R =,量具误差,Gage Error /,允差,Tolerance = 6.1 / 20 * 100 % = 30.5%,快速,GR&R（,短期模式）,d,常数表,允差,Tolerance = 20,=,最大值-最小值,R,R,R,R,R,46,短期模式练习,Average range = R = ( + + + + )/_ = _ / _,Gage Error = 5.15 / d * R = 5.15 /_ * R = _ * R = _ * _ = _,% Gage R&R = Gage Error / Tolerance = _ / _ * 100 %) = _%,Spec range = 185 - 215,47,短期与长期方法的比较,短期模式,用生产设备,用生产操作员,快速 - 只需几个样品(5),无反复（,replicates）,估计总的变差(,Total Gage R&R),不能区分,AV,和,EV,不能指导改进的方向,可用于破坏性测试,长期模式,用生产设备,用生产操作员,较多样品 (5),要求反复,Replicates (3),估计总的变差 (,Total Gage R&R),可以区分,AV,和,EV,为测量系统的改进提供指导,48,正常标准方法,Part,A,B,Test 1,Test 2,Operator,对同样的样品进行重复测量,(,称之为交叉设计,Crossed Designed),巢式设计,Nested Design,C,Test 1,Test 2,Test 1,Test 2,Operator,I,Operator,II,Operator,III,样品来自同一总体,Part,Test,A,B,C,1,2,1,2,1,2,D,E,F,1,2,1,2,1,2,G,H,I,1,2,1,2,1,2,I,II,III,破坏性测量和不可重复的测量,49,破坏性测量和不可重复的测量,与可重复测量的测量系统比较,样品的个数不是几个,(,例如,10,个,),而是几组,(,例如,10,组,),每组内样品的个数等于对该组要进行的破坏性测试的次数,每组样品来自过程中连续的产出,默认该组内各样品之间是没有差异的,MinitabStatQuality ToolsGage Study,Gage R&R Study (Nested),结果中只能看到测量系统的重复性,50,Gage R&R,%Contribution,Source VarComp (of VarComp),Total Gage R&R 0.0002311 2.31,Repeatability 0.0002311 2.31,Reproducibility 0.0000000 0.00,Part-To-Part 0.0097807 97.69,Total Variation 0.0100119 100.00,Study Var %Study Var,Source StdDev (SD) (6 * SD) (%SV),Total Gage R&R 0.015202 0.091214 15.19,Repeatability 0.015202 0.091214 15.19,Reproducibility 0.000000 0.000000 0.00,Part-To-Part 0.098898 0.593386 98.84,Total Variation 0.100059 0.600355 100.00,Number of Distinct Categories = 9,使用前面一样的数据,51,NO-GO,GO,Error,Operator 2,Operator 1,定性数据(,Attribute Data),的测量系统,52,定性数据(,Attribute Data),的测量系统的可靠性,Go-No Go,数据模式,人为因素主导，情况复杂,统计模型多种多样,统计学上各家争鸣，尚无定论,实践中采用何种形式，取决于实例与统计模型的接近程度,53,对于以,“,是,”,和,“,不是,”,为计数基础的定性数据，其,GR&R,考察的概念是与定量数据一样的。但方法上完全不同.,定性数据测量系统的能力取决于操作员判断的有效性，即将,“,合格,”,判断成合格，将,“,不合格,”,判断成不合格的程度.,计数型测量系统能力分析方法示例,54,以下为判断所用的指标,有效性,Effectiveness(E),-,即判断,“,合格,”,与,“,不合格,”,的准确性,E=,实际判断正确的次数/可能判断正确的机会次数,.,漏判的几率,Probability of miss(P-miss),-,将,“,不合格,”,判为合格的机会,P(miss)=,实际漏判的次数 / 漏判的总机会数,.,误判的几率,Probability of false alarm(P-FA),-,将,“,合格,”,判为不合格的机会.,P(false alarm)=,实际误判次数 / 误判的总机会数,.,偏倚,Bias(B),-,指漏判或误判的偏向.,B=P(false alarm) / P(miss),B=1,无偏倚,B1,偏向误判,BQuality ToolsAttribute Agreement Analysis,Between Appraisers,Assessment Agreement,# Inspected # Matched Percent 95 % CI,12 11 91.67 (61.52, 99.79),# Matched: All appraisers assessments agree with each other.,Fleiss Kappa Statistics,Response Kappa SE Kappa Z P(vs 0),F 0.798319 0.288675 2.76546 0.0028,P 0.798319 0.288675 2.76546 0.0028,62,ICC,等级关联系数,Intraclass Correlation Coefficient,当产品的质量判定不仅仅是合格与不合格两种性质，而是进行多个等级的区分时,ICC,针对不同情行下的测量系统进行评估,ICC,使用平方和,Sums of Square,来进行评估工作,实例：某公司建立评估系统来测量采购订单,(PO),完成的质量水平，选了三个高级采购员对个订单的完成好坏进行打分评估，分代表很差，分代表很好，结果如下,63,PO#,Buyer A,Buyer B,Buyer C,1,5,7,6,2,6,5,4,3,4,4,3,4,4,5,4,5,7,6,5,6,6,7,7,7,8,9,8,8,9,8,8,9,5,5,6,10,6,7,8,定义如下平方和项,BMS=Between mean square,EMS=Error mean square,JMS=Judge mean square,WMS=Within mean square,TMS=Total mean square,64,Sum of all squared: 1182,Average of all: 6.07,Sum X average=6.07X182=1110.81,Degree of freedom,Buyers=3-1=2,Between PO=10-1=9,Total=30-1=29,Within PO=10X(3-1)=20,Error=29-9-2=18,65,BMS=SS between POs/DF of POs=(3510/3-1110.81)/9=6.57,JMS=SS of Buyers/DF of Buyers=(11050/10-1110.81)/2=2.9,TMS=SS of all/DF of total=(1182-1110.81)/29=2.45,WMS=(SS total-SS between POs)/DF within POs,=(1182-1110.81)-(3510/3-1110.81)/20=0.6,EMS=(SS total-SS between PO-SS buyers)/DF of Error,=(1182-1110.81)-(3510/2-1110.81)-(11050/10-1110.81)/18,=(71.19-59.19-5.81)/18=0.344,66,三种情形下的,ICC,计算,任意从很多采购员中取,3,个人来对,1,个,PO,打分,下一个,PO,又重复同样的事,任意取,3,人来打分,每次打分的采购员可能不相同,每个采购员的可信度为：,(k,代表采购员的个数）,ICC=(BMS-WMS)/BMS+(k-1)WMS,=(6.57-0.6)/(6.57+2*0.6),=0.77,采购员的平均可信度为,ICC=(BMS-WMS)/BMS,=(6.57-0.6)/6.57,=0.91,67,2.,任意从很多采购员中取,3,人来对,10,个,PO,进行打分,鉴定,10,个,PO,的采购员是一样的,3,人,每个采购员的可信度为：（,n,代表的个数）,ICC=(BMS-EMS)/BMS+(k-1)EMS+k(JMS-EMS)/n,=(6.57-0.344)/6.57+2*0.344+3*(2.9-0.344)/10,=0.78,采购员的平均可信度为,ICC=(BMS-EMS)/BMS+(JMS-EMS)/n,=(6.57-0.344)/6.57+(2.9-0.344)/10,=0.91,68,3.,固定了,3,个采购员对,10,个,PO,进行打分,每个采购员的可信度为,ICC=(BMS-EMS)/BMS+(k-1)EMS,=(6.57-0.344)/6.57+(3-1)*0.344,=0.86,采购员的平均可信度为,ICC=(BMS-EMS)/BMS,=(6.57-0.344)/6.57,=0.95,ICC,的接收下限为,0.7, 0.9,以上比较好,69,练习,某食品公司生产辣酱，其产品的辣度由专业品辣员来担当。辣度分为,微辣,(M),辣,(H),很辣,(VH),受不了,(SH),为了保证辣度的测量是可靠的，找了两个品辣员对个样品进行品味，结果如下,70,Sauce,Taster 1,Taster 2,1,M,M,2,M,H,3,SH,VH,4,VH,SH,5,H,VH,6,VH,VH,7,H,M,8,H,H,9,SH,VH,10,M,H,计算三种情形下的,该公司辣度测量系统如何？,71,
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