Excel Report
Transfer Function  R= f(A,B,…) 10.1625 +.27625*A +.176875*B +.08275*C+D -.0010625*A*B +.0004125*B*C -.0000025*A*B*C
Data Entry Summary [R] [A] [B] [C] [D]
Variable Name Lenght HoldPres CycleTime MoldTemp DoE_Error
IV Distribution Type Normal Normal Normal Normal
IVD 1*Par Value (Nominal Mean) 130 100 150 0
IVD 2*Par Value (Nominal StDev) 3 2 1.5 0.212
IVD 3*Par Value (..) 0 0 0 0
Lower Spec Limit (IV*opt) 62.175 121 94 145.5
Upper Spec Limit (IV*opt) 65.175 139 106 154.5
Use/Priority in Solver (0 to 1) 1 1 1 0
Upper Z-LT Constrains (*opt) 4.5 4.5 4.5
Simulation Summary - Step 0 [R] [A] [B] [C] [D]
Variable Name Lenght HoldPres CycleTime MoldTemp DoE_Error
Mean 63.67504 130.0025 99.99995 149.9979 -0.00011
Standard Deviation 0.482044 2.998884 1.99888 1.498704 0.211741
Anderson-Darling 6.242015
P Value 0
Coeff. of Variability 0.00757 0.023068 0.019989 0.009991 -1905.22
Mean Std. Error 0.000482 0.002999 0.001999 0.001499 0.000212
Variance 0.232366 8.993306 3.995519 2.246114 0.044834
Skewness -0.0229 -4.8E-05 0.000825 -0.00229 -0.00061
Kurtosis 3.004012 3.00702 3.002638 3.003095 2.99592
Median 63.67668 130.0043 99.99858 149.9996 0.00003
IQ1 63.35131 127.9819 98.65265 148.9891 -0.14308
IQ3 64.00078 132.0232 101.3457 151.0081 0.142711
Range Minimum 61.38318 116.2697 90.50638 141.9111 -1.05655
Range Maximum 65.95884 143.8744 109.6986 158.2572 1.035401
Range Width 4.575654 27.60473 19.19226 16.34615 2.09195
Lower Spec Limit/Test 62.175 121 94 145.5 -0.636
Upper Spec Limit/Test 65.175 139 106 154.5 0.636
Ppk 1.037225 1.000089 1.000552 1.000406 1.00105
Pp 1.03725 1.000372 1.000561 1.000865 1.001225
PpL 1.037276 1.000655 1.000552 1.000406 1.00105
PpU 1.037225 1.000089 1.000569 1.001323 1.0014
Z-LT Value 3.111675 3.000266 3.001656 3.001218 3.00315
L-PPM 1013 1376 1367 1364 1316
U-PPM 864 1374 1299 1331 1306
PPM 1877 2750 2666 2695 2622
Prob @<LSL 0.001013 0.001376 0.001367 0.001364 0.001316
Prob @>USL 0.000864 0.001374 0.001299 0.001331 0.001306
Prob @>=LSL And <=@USL 0.998123 0.99725 0.997334 0.997305 0.997378
L-Area Items (1 Million base) 1013 1376 1367 1364 1316
R-Area Items(1 Million base) 864 1374 1299 1331 1306
C-Area Items(1 Million base) 998123 997250 997334 997305 997378
Variable [R] [A] [B] [C] [D]
Contribution to Variance 0 0.679901 4.61E-02 0.081277 0.192673
M [..] [R] [A] [B] [C] [D]
Pearson [R].. [Var(N)) 1 0.824432 0.214788 0.285047 0.438877
Pearson [A].. [Var(N)) 1 -2.36E-04 7.63E-04 -1.44E-04
Pearson [B].. [Var(N)) 1 5.52E-04 -6.71E-04
Pearson [C].. [Var(N)) 1 -3.95E-04
Pearson [D].. [Var(N)) 1
5D CubeSpace Analysis © -  40 populated on  243 possible HyperCubes
HyperCube Items
[<R_f(<A,<B,=C,=D)] 4
[<R_f(<A,=B,=C,<D)] 1
[<R_f(<A,=B,=C,=D)] 344
[<R_f(=A,<B,=C,=D)] 9
[<R_f(=A,=B,<C,=D)] 10
[<R_f(=A,=B,=C,<D)] 47
[<R_f(=A,=B,=C,=D)] 598
[=R_f(<A,=B,=C,=D)] 1022
[=R_f(<A,=B,=C,>D)] 1
[=R_f(<A,>B,=C,=D)] 4
[=R_f(=A,<B,<C,=D)] 3
[=R_f(=A,<B,=C,<D)] 1
[=R_f(=A,<B,=C,=D)] 1349
[=R_f(=A,<B,>C,=D)] 1
[=R_f(=A,=B,<C,<D)] 2
[=R_f(=A,=B,<C,=D)] 1341
[=R_f(=A,=B,<C,>D)] 1
[=R_f(=A,=B,=C,<D)] 1257
[=R_f(=A,=B,=C,=D)] 988246
[=R_f(=A,=B,=C,>D)] 1260
[=R_f(=A,=B,>C,<D)] 4
[=R_f(=A,=B,>C,=D)] 1304
[=R_f(=A,=B,>C,>D)] 1
[=R_f(=A,>B,<C,=D)] 2
[=R_f(=A,>B,=C,<D)] 1
[=R_f(=A,>B,=C,=D)] 1286
[=R_f(=A,>B,=C,>D)] 1
[=R_f(=A,>B,>C,=D)] 2
[=R_f(>A,=B,<C,=D)] 5
[=R_f(>A,=B,=C,<D)] 3
[=R_f(>A,=B,=C,=D)] 1026
[>R_f(=A,=B,=C,=D)] 467
[>R_f(=A,=B,=C,>D)] 38
[>R_f(=A,=B,>C,=D)] 16
[>R_f(=A,=B,>C,>D)] 1
[>R_f(=A,>B,=C,=D)] 2
[>R_f(>A,=B,=C,=D)] 334
[>R_f(>A,=B,=C,>D)] 3
[>R_f(>A,=B,>C,=D)] 2
[>R_f(>A,>B,=C,=D)] 1
Defects Pareto Analysis:  16 HyperCubes found
DF_HyperCube DF_Items Cum_DF
[<R_f(=A,=B,=C,=D)] 598 598
[>R_f(=A,=B,=C,=D)] 467 1065
[<R_f(<A,=B,=C,=D)] 344 1409
[>R_f(>A,=B,=C,=D)] 334 1743
[<R_f(=A,=B,=C,<D)] 47 1790
[>R_f(=A,=B,=C,>D)] 38 1828
[>R_f(=A,=B,>C,=D)] 16 1844
[<R_f(=A,=B,<C,=D)] 10 1854
[<R_f(=A,<B,=C,=D)] 9 1863
[<R_f(<A,<B,=C,=D)] 4 1867
[>R_f(>A,=B,=C,>D)] 3 1870
[>R_f(=A,>B,=C,=D)] 2 1872
[>R_f(>A,=B,>C,=D)] 2 1874
[>R_f(>A,>B,=C,=D)] 1 1875
[>R_f(=A,=B,>C,>D)] 1 1876
[<R_f(<A,=B,=C,<D)] 1 1877
Ppm StDev[R] StDev[A] StDev[B] StDev[C] StDev[D]
1057 0.45682 2.77925 1.95982 1.45967 0.211741
937 0.452165 2.738773 1.951058 1.450887 0.211741
888 0.449983 2.719941 1.946432 1.446177 0.211741
833 0.448052 2.703302 1.942214 1.441873 0.211741
788 0.446081 2.686289 1.937897 1.437479 0.211741
743 0.444071 2.668911 1.93348 1.432995 0.211741
691 0.441975 2.650749 1.928875 1.428335 0.211741
649 0.439746 2.631383 1.923991 1.423411 0.211741
595 0.437433 2.611247 1.918911 1.418306 0.211741
553 0.434942 2.589497 1.913451 1.412842 0.211741
521 0.432369 2.566989 1.907782 1.407188 0.211741
482 0.429579 2.542501 1.901633 1.401083 0.211741
440 0.426619 2.51645 1.895079 1.394602 0.211741
393 0.423398 2.488007 1.887921 1.387557 0.211741
334 0.419916 2.45716 1.880131 1.379925 0.211741
303 0.416075 2.423 1.871471 1.371484 0.211741
274 0.411802 2.384834 1.861735 1.362046 0.211741
229 0.406965 2.341438 1.850568 1.351284 0.211741
184 0.401319 2.290493 1.837307 1.338588 0.211741
146 0.39443 2.227903 1.820754 1.322856 0.211741
StD[R] .357645207425801 +3.42590858802634E-4*Ppm^1 -7.54759372246905E-7*Ppm^2 +1.06555545248007E-9*Ppm^3 -7.94472867600446E-13*Ppm^4 +2.3776448342893E-16*Ppm^5
R2 Eq[R] 0.999334
StD[A] 1.89141399108619 +3.14914499379761E-3*Ppm^1 -7.0319633351981E-6*Ppm^2 +9.94034776742119E-9*Ppm^3 -7.40515993083058E-12*Ppm^4 +2.21361966117493E-15*Ppm^5
R2 Eq[A] 0.999327
StD[B] 1.73158431906625 +8.39121594764452E-4*Ppm^1 -1.89284689251383E-6*Ppm^2 +2.63421650334653E-9*Ppm^3 -1.90634306428387E-12*Ppm^4 +5.49450192165397E-16*Ppm^5
R2 Eq[B] 0.999316
StD[C] 1.2388704211528 +7.85823408587708E-4*Ppm^1 -1.74423392231093E-6*Ppm^2 +2.41923294677876E-9*Ppm^3 -1.74621778224425E-12*Ppm^4 +5.01599289481216E-16*Ppm^5
R2 Eq[C] 0.999326
StD[D] 0.212
R2 Eq[D] ***
Equations Validity Range (Ppm) 146 1057
Simulation Summary - Step 20 [R] [A] [B] [C] [D]
Variable Name Lenght HoldPres CycleTime MoldTemp DoE_Error
Mean 63.67498 130.002 99.99995 149.9981 -0.00011
Standard Deviation 0.408034 2.351393 1.852268 1.352758 0.211741
Anderson-Darling 4.770718
P Value 0
Coeff. of Variability 0.006408 0.018087 0.018523 0.009018 -1905.22
Mean Std. Error 0.000408 0.002351 0.001852 0.001353 0.000212
Variance 0.166492 5.529049 3.430898 1.829953 0.044834
Skewness -0.01996 -4.8E-05 0.000825 -0.00229 -0.00061
Kurtosis 3.002532 3.00702 3.002638 3.003095 2.99592
Median 63.67595 130.0033 99.99868 149.9996 0.00003
IQ1 63.40061 128.4176 98.75148 149.0876 -0.14308
IQ3 63.9508 131.5864 101.247 150.9099 0.142711
Range Minimum 61.76136 119.2342 91.20271 142.6988 -1.05655
Range Maximum 65.58615 140.8788 108.9873 157.4531 1.035401
Range Width 3.824782 21.64457 17.78457 14.75433 2.09195
Lower Spec Limit/Test 62.175 121 94 145.5 -0.636
Upper Spec Limit/Test 65.175 139 106 154.5 0.636
Ppk 1.225372 1.275556 1.079749 1.108387 1.00105
Pp 1.225387 1.27584 1.079757 1.108846 1.001225
PpL 1.225372 1.276123 1.079749 1.108387 1.00105
PpU 1.225402 1.275556 1.079766 1.109305 1.0014
Z-LT Value 3.676117 3.826669 3.239246 3.325162 3.00315
L-PPM 132 59 637 446 1316
U-PPM 109 78 577 456 1306
PPM 241 137 1214 902 2622
Prob @<LSL 0.000132 0.000059 0.000637 0.000446 0.001316
Prob @>USL 0.000109 0.000078 0.000577 0.000456 0.001306
Prob @>=LSL And <=@USL 0.999759 0.999863 0.998786 0.999098 0.997378
L-Area Items (1 Million base) 132 59 637 446 1316
R-Area Items(1 Million base) 109 78 577 456 1306
C-Area Items(1 Million base) 999759 999863 998786 999098 997378
Variable [R] [A] [B] [C] [D]
Contribution to Variance 0 0.583382 5.53E-02 9.24E-02 0.26896
M [..] [R] [A] [B] [C] [D]
Pearson [R].. [Var(N)) 1 0.763682 0.235135 0.303852 0.518538
Pearson [A].. [Var(N)) 1 -2.36E-04 7.63E-04 -1.44E-04
Pearson [B].. [Var(N)) 1 5.52E-04 -6.71E-04
Pearson [C].. [Var(N)) 1 -3.95E-04
Pearson [D].. [Var(N)) 1
5D CubeSpace Analysis © -  23 populated on  243 possible HyperCubes
HyperCube Items
[<R_f(<A,=B,=C,=D)] 10
[<R_f(=A,<B,=C,=D)] 2
[<R_f(=A,=B,<C,=D)] 2
[<R_f(=A,=B,=C,<D)] 19
[<R_f(=A,=B,=C,=D)] 99
[=R_f(<A,=B,=C,=D)] 49
[=R_f(=A,<B,=C,<D)] 1
[=R_f(=A,<B,=C,=D)] 634
[=R_f(=A,=B,<C,=D)] 444
[=R_f(=A,=B,=C,<D)] 1294
[=R_f(=A,=B,=C,=D)] 994957
[=R_f(=A,=B,=C,>D)] 1287
[=R_f(=A,=B,>C,=D)] 452
[=R_f(=A,=B,>C,>D)] 1
[=R_f(=A,>B,=C,<D)] 1
[=R_f(=A,>B,=C,=D)] 575
[=R_f(=A,>B,=C,>D)] 1
[=R_f(>A,=B,=C,<D)] 1
[=R_f(>A,=B,=C,=D)] 62
[>R_f(=A,=B,=C,=D)] 74
[>R_f(=A,=B,=C,>D)] 17
[>R_f(=A,=B,>C,=D)] 3
[>R_f(>A,=B,=C,=D)] 15
Defects Pareto Analysis:  9 HyperCubes found
DF_HyperCube DF_Items Cum_DF
[<R_f(=A,=B,=C,=D)] 99 99
[>R_f(=A,=B,=C,=D)] 74 173
[<R_f(=A,=B,=C,<D)] 19 192
[>R_f(=A,=B,=C,>D)] 17 209
[>R_f(>A,=B,=C,=D)] 15 224
[<R_f(<A,=B,=C,=D)] 10 234
[>R_f(=A,=B,>C,=D)] 3 237
[<R_f(=A,=B,<C,=D)] 2 239
[<R_f(=A,<B,=C,=D)] 2 241
Data Comparison [R] [A] [B] [C] [D]
Variable Name Lenght HoldPres CycleTime MoldTemp DoE_Error
Nominal Value 63.675 130 100 150 0
Starting [R] Ppm 1877 1877 1877 1877 1877
Starting Mean 63.67504 130.0025 99.99995 149.9979 -0.00011
Starting StDev 0.482044 2.998884 1.99888 1.498704 0.211741
Starting Tolerance (±) 1.446131 9 6 4.5 0.636
Starting LSL 62.175 121 94 145.5 -0.636
Starting USL 65.175 139 106 154.5 0.636
Pp 1.03725 1.000372 1.000561 1.000865 1.001225
Target [R] Ppm 241 241 241 241 241
Estimated Mean 63.67498 130.002 99.99995 149.9981 -0.00011
Estimated StDev 0.408034 2.351393 1.852268 1.352758 0.211741
Estimated Tolerance (±) 1.224103 7.054179 5.556805 4.058273 0.635222
LSL / Suggested LSL (Pp=1) 62.175 122.9478 94.44315 145.9399 -0.63533
USL / Suggested USL (Pp=1) 65.175 137.0562 105.5568 154.0564 0.635111
Pp [Base Limits] 1.225387 1.27584 1.079757 1.108846 1.001225
Pp [Suggested Limits] 1 1 1 1
Defect Reduction % 87.16036
StDev Reduction % 15.35325 21.59107 7.334674 9.738182 0
 
 
Minitab Project Report
 
 —————   11/04/2006 11:15:52   ———————————————————— 
 
Welcome to Minitab, press F1 for help.
 
Results for: MTBdgSheet1 - Minitab MC Simulation (8000 Els)
 
Row   Els     Mean     StDev  Mean_BoxCox  StDev_BoxCox  Est_Pp_BoxCox  Est_<LSL_BoxCox  Est_>USL_BoxCox  Est_PpmTotal_BoxCox
  1  8000  63.6759  0.482665      30887.3       582.583        1.03605          1102.38          802.134              1904.52
**************************************************************************
Transfer Function: [R] = 10.1625 +.27625*A +.176875*B +.08275*C+D -.0010625*A*B +.0004125*B*C -.0000025*A*B*C
See annexed docs for more info...
 Starting Champion of Italy ® MC Simulation - 1. Million Els
... please wait during the elaboration ...
**************************************************************************
 
Results for: MTBdgSheet3 - Champion of Italy MC Simulation (1000000 Els)
 
                                                                                Mean
                          Standard                               Coeff. of      Std.
Row  Labels        Mean  Deviation  Anderson-Darling  P Value  Variability     Error  Variance   Skewness  Kurtosis   Median
  1  Lenght      63.675    0.48204           6.24202        0         0.01  0.000482   0.23237  -0.022898   3.00401   63.677
  2  HoldPres   130.003    2.99888                 *        *         0.02  0.002999   8.99331  -0.000048   3.00702  130.004
  3  CycleTime  100.000    1.99888                 *        *         0.02  0.001999   3.99552   0.000825   3.00264   99.999
  4  MoldTemp   149.998    1.49870                 *        *         0.01  0.001499   2.24611  -0.002286   3.00310  150.000
  5  DoE_Error   -0.000    0.21174                 *        *     -1905.22  0.000212   0.04483  -0.000611   2.99592    0.000
                         Range    Range               Lower Spec  Upper Spec
Row      IQ1      IQ3  Minimum  Maximum  Range Width  Limit/Test  Limit/Test      Ppk       Pp      PpL      PpU  Z-LT Value  L-PPM
  1   63.351   64.001   61.383   65.959       4.5757      62.175      65.175  1.03723  1.03725  1.03728  1.03723     3.11168   1013
  2  127.982  132.023  116.270  143.874      27.6047     121.000     139.000  1.00009  1.00037  1.00066  1.00009     3.00027   1376
  3   98.653  101.346   90.506  109.699      19.1923      94.000     106.000  1.00055  1.00056  1.00055  1.00057     3.00166   1367
  4  148.989  151.008  141.911  158.257      16.3461     145.500     154.500  1.00041  1.00087  1.00041  1.00132     3.00122   1364
  5   -0.143    0.143   -1.057    1.035       2.0920      -0.636       0.636  1.00105  1.00123  1.00105  1.00140     3.00315   1316
                                                     L-Area
                                              Prob    Items
                                            @>=LSL       (1
                                               And  Million
Row  U-PPM   PPM  Prob @<LSL  Prob @>USL    <=@USL    base)
  1    864  1877    0.001013    0.000864  0.998123     1013
  2   1374  2750    0.001376    0.001374  0.997250     1376
  3   1299  2666    0.001367    0.001299  0.997334     1367
  4   1331  2695    0.001364    0.001331  0.997305     1364
  5   1306  2622    0.001316    0.001306  0.997378     1316
Results for: MTBdgSheet5 - HyperCubes Report
 
**************************************************************************
 Starting Champion of Italy ® 20 Steps Equations Optimizer
Creating Equations ... please wait ...
**************************************************************************
**************************************************************************
HyperSpace Defects Optimization done - 48.562 sec required. (2.428/Step)
Best Equations: StD(V)= f(Ppm[R]) - Variable(s) StDeviation as function of Response Defects (Ppm)
StD[R] .357645207425801 +3.42590858802634E-4*Ppm^1 -7.54759372246905E-7*Ppm^2 +1.06555545248007E-9*Ppm^3 -7.94472867600446E-13*
Ppm^4 +2.3776448342893E-16*Ppm^5
R2 Eq[R] 0.999334
StD[A] 1.89141399108619 +3.14914499379761E-3*Ppm^1 -7.0319633351981E-6*Ppm^2 +9.94034776742119E-9*Ppm^3 -7.40515993083058E-12*P
pm^4 +2.21361966117493E-15*Ppm^5
R2 Eq[A] 0.999327
StD[B] 1.73158431906625 +8.39121594764452E-4*Ppm^1 -1.89284689251383E-6*Ppm^2 +2.63421650334653E-9*Ppm^3 -1.90634306428387E-12*
Ppm^4 +5.49450192165397E-16*Ppm^5
R2 Eq[B] 0.999316
StD[C] 1.2388704211528 +7.85823408587708E-4*Ppm^1 -1.74423392231093E-6*Ppm^2 +2.41923294677876E-9*Ppm^3 -1.74621778224425E-12*P
pm^4 +5.01599289481216E-16*Ppm^5
R2 Eq[C] 0.999326
StD[D] .212
R2 Eq[D] ***
Equations Validity Range (Ppm) 146 1057
**************************************************************************
 
Results for: MTBdgSheet6 - Champion of Italy Optimized Equations
The regression equation is
StDev[A] = 2.009 + 0.001805 Ppm - 0.000002 Ppm**2 + 0.000000 Ppm**3
S = 0.00608431   R-Sq = 99.9%   R-Sq(adj) = 99.8%
 
Analysis of Variance
Source      DF        SS        MS        F      P
Regression   3  0.466693  0.155564  4202.30  0.000
Error       16  0.000592  0.000037
Total       19  0.467285
 
Sequential Analysis of Variance
Source     DF        SS       F      P
Linear      1  0.441765  311.59  0.000
Quadratic   1  0.022290  117.32  0.000
Cubic       1  0.002638   71.25  0.000
 
The regression equation is
StDev[B] = 1.765 + 0.000462 Ppm - 0.000000 Ppm**2 + 0.000000 Ppm**3
S = 0.00172652   R-Sq = 99.8%   R-Sq(adj) = 99.8%
 
Analysis of Variance
Source      DF         SS         MS        F      P
Regression   3  0.0298921  0.0099640  3342.66  0.000
Error       16  0.0000477  0.0000030
Total       19  0.0299398
Sequential Analysis of Variance
Source     DF         SS       F      P
Linear      1  0.0281733  287.08  0.000
Quadratic   1  0.0015507  122.20  0.000
Cubic       1  0.0001680   56.37  0.000
 
The regression equation is
StDev[C] = 1.270 + 0.000438 Ppm - 0.000000 Ppm**2 + 0.000000 Ppm**3
S = 0.00164380   R-Sq = 99.9%   R-Sq(adj) = 99.8%
Analysis of Variance
Source      DF         SS         MS        F      P
Regression   3  0.0290909  0.0096970  3588.69  0.000
Error       16  0.0000432  0.0000027
Total       19  0.0291341
 
Sequential Analysis of Variance
Source     DF         SS       F      P
Linear      1  0.0275691  317.08  0.000
Quadratic   1  0.0013813  127.79  0.000
Cubic       1  0.0001405   52.00  0.000
**************************************************************************
Now a new MC Simulation to test (verify) the target of 236. Ppm (Response Defects)
using [Ind_Var] values gotten from Optimized Equations.
MonteCarlo Simulation Prediction Interval : MC PI95% From 207. To 263.
[Ind_Var] Standard Deviations used in next simulation, will be :
[A] : 2.35226787265237
[B] : 1.85330651298759
[C] : 1.35392727715093
[D] : .212 * FIX *
**************************************************************************
 
 
Results for: MTBdgSheet7 - Minitab MC Simulation (8000 Els)
 
Row   Els     Mean     StDev  Mean_BoxCox  StDev_BoxCox  Est_Pp_BoxCox  Est_<LSL_BoxCox  Est_>USL_BoxCox  Est_PpmTotal_BoxCox
  1  8000  63.6742  0.408396      98071.0       1740.15        1.22457          158.569          89.6443              248.213
 
Results for: MTBdgSheet9 - Champion of Italy MC Simulation (1000000 Els)
 
                                                                                Mean
                          Standard                               Coeff. of      Std.
Row  Labels        Mean  Deviation  Anderson-Darling  P Value  Variability     Error  Variance   Skewness  Kurtosis   Median
  1  Lenght      63.675    0.40803           4.77072        0         0.01  0.000408   0.16649  -0.019962   3.00253   63.676
  2  HoldPres   130.002    2.35139                 *        *         0.02  0.002351   5.52905  -0.000048   3.00702  130.003
  3  CycleTime  100.000    1.85227                 *        *         0.02  0.001852   3.43090   0.000825   3.00264   99.999
  4  MoldTemp   149.998    1.35276                 *        *         0.01  0.001353   1.82995  -0.002286   3.00310  150.000
  5  DoE_Error   -0.000    0.21174                 *        *     -1905.22  0.000212   0.04483  -0.000611   2.99592    0.000
 
                         Range    Range               Lower Spec  Upper Spec
Row      IQ1      IQ3  Minimum  Maximum  Range Width  Limit/Test  Limit/Test      Ppk       Pp      PpL      PpU  Z-LT Value  L-PPM
  1   63.401   63.951   61.761   65.586       3.8248      62.175      65.175  1.22537  1.22539  1.22537  1.22540     3.67612    132
  2  128.418  131.586  119.234  140.879      21.6446     121.000     139.000  1.27556  1.27584  1.27612  1.27556     3.82667     59
  3   98.751  101.247   91.203  108.987      17.7846      94.000     106.000  1.07975  1.07976  1.07975  1.07977     3.23925    637
  4  149.088  150.910  142.699  157.453      14.7543     145.500     154.500  1.10839  1.10885  1.10839  1.10931     3.32516    446
  5   -0.143    0.143   -1.057    1.035       2.0920      -0.636       0.636  1.00105  1.00123  1.00105  1.00140     3.00315   1316
 
                                                     L-Area
                                              Prob    Items
                                            @>=LSL       (1
                                               And  Million
Row  U-PPM   PPM  Prob @<LSL  Prob @>USL    <=@USL    base)
  1    109   241    0.000132    0.000109  0.999759      132
  2     78   137    0.000059    0.000078  0.999863       59
  3    577  1214    0.000637    0.000577  0.998786      637
  4    456   902    0.000446    0.000456  0.999098      446
  5   1306  2622    0.001316    0.001306  0.997378     1316
Results for: MTBdgSheet14 - Variation Reduction
 
**************************************************************************
For correct comparison between Minitab and Champion of Italy results...
please remenber that:
- Kurtosis algo is different between Minitab and Champion of Italy ...
- (**) do not compare absolute Ppm values from simulations with DIFFERENT ELS SIZE ...
  but compare only simulations with same els size ...
  (use Save Data to Minitab Worksheet option to do it)
- RNGeneration CANNOT BE NEVER exactly the same between the two softwares ...
- If BoxCox transformation is used, FORCE the same lambda for correct values comparison.
**************************************************************************
**************************************************************************
 
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**************************************************************************
 
Minitab Graph Output

 

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