proj mani

Analysis Top kerf Width

Response 1 top KW ANOVA for Response Surface Reduced Cubic ModelAnalysis of variance table [Partial sum of squares - Type III]

Sum of Mean F p-valueSource Squares df Square Value Prob > FModel 0.22 12 0.018 3.32 0.1285 not

significantA-power 0.089 1 0.089 16.27 0.0157B-cutting speed 9.801E-003 1 9.801E-003 1.78 0.2527C-gas pressure 9.216E-003 1 9.216E-003 1.68 0.2650

AB 3.422E-004 1 3.422E-004 0.062 0.8152AC 0.015 1 0.015 2.80 0.1697BC 0.019 1 0.019 3.47 0.1362A2 0.019 1 0.019 3.53 0.1335B2 4.753E-004 1 4.753E-004 0.086 0.7833C2 0.041 1 0.041 7.53 0.0517

A2B 0.010 1 0.010 1.87 0.2429A2C 4.705E-003 1 4.705E-003 0.86 0.4072AB2 0.020 1 0.020 3.66 0.1284

Pure Error 0.022 4 5.495E-003Cor Total 0.24 16

The "Model F-value" of 3.32 implies the model is not significant relative to the noise. There is a12.85 % chance that a "Model F-value" this large could occur due to noise.

Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.

Std. Dev. 0.074 R-Squared 0.9087Mean 0.47 Adj R-Squared 0.6348C.V. % 15.82 Pred R-Squared N/APRESS N/A Adeq Precision 6.525 Case(s) with leverage of 1.0000: Pred R-Squared and PRESS statistic not defined

"Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 6.525 indicates an adequate signal. This model can be used to navigate the design space.

Coefficient Standard 95% CI 95% CIFactor Estimate df Error Low High VIF Intercept 0.39 1 0.033 0.30 0.49

A-power -0.15 1 0.037 -0.25 -0.047 2.00 B-cutting speed 0.050 1 0.037 -0.053 0.15 2.00 C-gas pressure 0.048 1 0.037 -0.055 0.15 2.00 AB9.250E-003 1 0.037 -0.094 0.11 1.00 AC-0.062 1 0.037 -0.16 0.041 1.00 BC0.069 1 0.037 -0.034 0.17 1.00 A20.068 1 0.036 -0.032 0.17 1.01 B2-0.011 1 0.036 -0.11 0.090 1.01 C20.099 1 0.036 -1.180E-003 0.20 1.01 A2 B-0.072 1 0.052 -0.22 0.074 2.00 A2 C-0.048 1 0.052 -0.19 0.097 2.00 AB20.10 1 0.052 -0.045 0.25 2.00

Final Equation in Terms of Actual Factors:

TOP KW = 8.40503-2.33756E-003 * power+1.62637E-003 * cutting speed-20.99000 * gas pressure-4.62500E-007 * power * cutting speed +2.29000E-003 * power * gas pressure+6.90000E-004

* cutting speed * gas pressure+7.78750E-007* power2-3.11375E-007 * cutting speed2+9.91250 * gas pressure2

-7.17500E-011 * power2 * cutting speed-4.85000E-007 * power2 * gas pressure+1.00250E-010 * power * cutting speed2

The Diagnostics Case Statistics Report has been moved to the Diagnostics Node. In the Diagnostics Node, Select Case Statistics from the View Menu.

Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the: 1) Normal probability plot of the studentized residuals to check for normality of residuals. 2) Studentized residuals versus predicted values to check for constant error. 3) Externally Studentized Residuals to look for outliers, i.e., influential values. 4) Box-Cox plot for power transformations.

If all the model statistics and diagnostic plots are OK, finish up with the Model Graphs icon.

Design-Expert® Software

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X1 = A: powerX2 = B: cutting speed

Actual FactorC: gas pressure = 0.80

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top KW0.773

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Bottom Kerf Width

Response 2 bottom KW ANOVA for Response Surface Reduced Cubic ModelAnalysis of variance table [Partial sum of squares - Type III]

Sum of Mean F p-valueSource Squares df Square Value Prob > F

Model 0.12 12 9.720E-003 1.63 0.3395 not significant

A-power 0.020 1 0.020 3.42 0.1379B-cutting speed 1.056E-003 1 1.056E-003 0.18 0.6957C-gas pressure 0.019 1 0.019 3.17 0.1498AB2.025E-003 1 2.025E-003 0.34 0.5916AC9.000E-006 1 9.000E-006 1.507E-003 0.9709BC0.012 1 0.012 2.01 0.2294A21.242E-003 1 1.242E-003 0.21 0.6720B27.632E-003 1 7.632E-003 1.28 0.3214C20.024 1 0.024 4.03 0.1152A2B0.010 1 0.010 1.70 0.2622A2C0.033 1 0.033 5.55 0.0780AB20.018 1 0.018 2.96 0.1605Pure Error 0.024 4 5.971E-003Cor Total 0.14 16


Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case there are no significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.



Coefficient Standard 95% CI 95% CIFactor Estimate df Error Low High VIF Intercept 0.25 1 0.035 0.16 0.35

A-power -0.072 1 0.039 -0.18 0.036 2.00 B-cutting speed -0.016 1 0.039 -0.12 0.091 2.00 C-gas pressure 0.069 1 0.039 -0.039 0.18 2.00 AB0.022 1 0.039 -0.085 0.13 1.00 AC1.500E-003 1 0.039 -0.11 0.11 1.00 BC0.055 1 0.039 -0.053 0.16 1.00 A2-0.017 1 0.038 -0.12 0.087 1.01 B20.043 1 0.038 -0.062 0.15 1.01 C20.076 1 0.038 -0.029 0.18 1.01 A2 B0.071 1 0.055 -0.080 0.22 2.00 A2 C-0.13 1 0.055 -0.28 0.023 2.00 AB20.094 1 0.055 -0.058 0.25 2.00


BOTTOM KW =+8.52122 -2.43445E-003 * power+2.27432E-003 * cutting speed -25.50075 * gas pressure -1.25100E-006 * power * cutting speed +7.74000E-003 * power * gas pressure+5.47500E-004 * cutting speed * gas pressure+6.92200E-007 * power2-2.39425E-007 * cutting speed2+7.55750 * gas pressure2+0.000000

* power2 * cutting speed-1.28750E-006 * power2 * gas pressure+9.40000E-011 * power * cutting speed2





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Kerf Taper

Response 3 Kt ANOVA for Response Surface Reduced Cubic ModelAnalysis of variance table [Partial sum of squares - Type III]


Model 59.45 12 4.95 1.80 0.3004A-power 8.84 1 8.84 3.22 0.1473B-cutting speed 6.30 1 6.30 2.29 0.2046C-gas pressure 0.62 1 0.62 0.23 0.6586AB0.25 1 0.25 0.092 0.7763AC5.89 1 5.89 2.14 0.2171BC0.29 1 0.29 0.11 0.7610A211.26 1 11.26 4.10 0.1130B24.28 1 4.28 1.56 0.2803C20.88 1 0.88 0.32 0.6012A2B14.88 1 14.88 5.41 0.0805A2C4.69 1 4.69 1.71 0.2614AB20.026 1 0.026 9.582E-003 0.9267Pure Error 10.99 4 2.75Cor Total 70.44 16


Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case there are no significant model terms. Values greater than 0.1000 indicate the model terms are not significant.

If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.



Coefficient Standard 95% CI 95% CI Factor Estimate df Error Low High

Intercept 2.66 1 0.74 0.60 4.72 A-power -1.49 1 0.83 -3.79 0.81 B-cutting speed 1.25 1 0.83 -1.05 3.56 C-gas pressure -0.40 1 0.83 -2.70 1.91 AB-0.25 1 0.83 -2.55 2.05 AC-1.21 1 0.83 -3.51 1.09 BC0.27 1 0.83 -2.03 2.57 A21.64 1 0.81 -0.61 3.88 B2-1.01 1 0.81 -3.25 1.24 C20.46 1 0.81 -1.79 2.70 A2 B -2.73 1 1.17 -5.98 0.53 A2 C 1.53 1 1.17 -1.72 4.79 AB2 0.11 1 1.17 -3.14 3.37


Kt =-1.34766+1.74619E-003 * power-0.012527 * cutting speed+84.89500 * gas pressure+1.50802E-005 * power * cutting speed-0.10404 * power * gas pressure+2.70000E-003 * cutting speed * gas pressure+1.65512E-006* power2-1.35213E-006 * cutting speed2+45.78750 * gas pressure2-2.72750E-009

* power2 * cutting speed+1.53175E-005 * power2 * gas pressure+0.000000 * power * cutting speed2





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Deviation

Response 4 Deviation ANOVA for Response Surface Reduced Cubic ModelAnalysis of variance table [Partial sum of squares - Type III]


Model 0.89 12 0.074 44.05 0.0012A-power 0.18 1 0.18 105.20 0.0005B-cutting speed 2.500E-005 1 2.500E-005 0.015 0.9087C-gas pressure 2.025E-003 1 2.025E-003 1.21 0.3335AB0.073 1 0.073 43.48 0.0027AC0.090 1 0.090 53.67 0.0018BC0.011 1 0.011 6.58 0.0624A20.20 1 0.20 120.49 0.0004B20.012 1 0.012 7.17 0.0553C20.032 1 0.032 18.81 0.0123A2B3.125E-004 1 3.125E-004 0.19 0.6882A2C0.16 1 0.16 95.19 0.0006AB20.15 1 0.15 86.95 0.0007Pure Error 6.707E-003 4 1.677E-003Cor Total 0.89 16

The Model F-value of 44.05 implies the model is significant. There is only

a 0.12% chance that a "Model F-Value" this large could occur due to noise.

Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, AB, AC, A2, C2, A2C, AB2 are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.



Coefficient Standard 95% CI 95% CIFactor Estimate df Error Low High

Intercept 0.044 1 0.018 -6.445E-003 0.095 A-power -0.21 1 0.020 -0.27 -0.15 B-cutting speed -2.500E-003 1 0.020 -0.059 0.054 C-gas pressure -0.023 1 0.020 -0.079 0.034 AB0.14 1 0.020 0.078 0.19 AC-0.15 1 0.020 -0.21 -0.093 BC-0.053 1 0.020 -0.11 4.346E-003 A20.22 1 0.020 0.16 0.27 B2-0.053 1 0.020 -0.11 1.957E-003 C20.087 1 0.020 0.031 0.14 A2 B -0.012 1 0.029 -0.093 0.068 A2 C 0.28 1 0.029 0.20 0.36 AB2 0.27 1 0.029 0.19 0.35


Deviation =-32.60981+0.017758 * power+7.67105E-003 * cutting speed+18.21450 * gas pressure-2.22000E-006 * power * cutting speed-0.018450 * power * gas pressure-5.25000E-004 * cutting speed *

gas pressure-1.98470E-006 * power2-8.63450E-007 * cutting speed2+8.65500 * gas pressure2+0.000000 * power2 * cutting speed+2.82500E-006 * power2 * gas pressure+2.70000E-010 * power * cutting speed2


Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the: 1) Normal probability plot of the studentized residuals to check for normality of residuals.

2) Studentized residuals versus predicted values to check for constant error. 3) Externally Studentized Residuals to look for outliers, i.e., influential values. 4) Box-Cox plot for power transformations.



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proj mani

Documents

normal probability plot

gas pressure ab0

select case statistics

externally studentized residuals

adeq precision case

insignificant model terms

model graphs icon

significant model terms