design and analysis of experiments (7) response surface methods and designs (2)

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Design and Analysis of Experiments (7) Response Surface Methods and Designs (2) Kyung-Ho Park

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Design and Analysis of Experiments (7) Response Surface Methods and Designs (2). Kyung-Ho Park. Steps to optimize a process. ③. Region of the optimum. ②. Temperature. Path of Improvement. current operating condition. 90%. ①. 80%. 60%. 60%. Time. Steps to optimize a process - PowerPoint PPT Presentation

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Page 1: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Design and Analysis of Experiments (7)

Response Surface Methods and Designs

(2)Kyung-Ho Park

Page 2: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Steps to optimize a processTe

mpe

ratu

re

Time

currentoperatingcondition

Regionof theoptimum

60% 60% 80%

90%Path ofImprovement

Page 3: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Steps to optimize a process

1. Sequential ExperimentsFactorial Design

2. Method of Steepest Ascent

3. Augmenting DesignResponse Surface Methods and Designs

Page 4: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

current operating condition time : 75 min temperature : 130℃

Obtain the maximum yield at Chemical Plant

22 Factorial Design

Time

Tem

pera

ture

8070127.5

75, 130 (3times)

132.5

Page 5: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Factorial DesignFactor: 2, level:2, Center Pt: 3

StdOrder RunOrder CenterPt Blocks time temperature Yield

1 5 1 1 70 127.5 54.3

2 4 1 1 80 127.5 60.3

3 1 1 1 70 132.5 64.6

4 6 1 1 80 132.5 68

5 2 0 1 75 130 60.3

6 3 0 1 75 130 64.3

7 7 0 1 75 130 62.3

Page 6: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Factorial Design

Term

Standardized Effect

AB

A

B

543210

4.303Factor NameA timeB temperature

Pareto Chart of the Standardized Effects(response is Yield, Alpha = .05)

Page 7: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Factors: 2 Base Design: 2, 4Runs: 7 Replicates: 1Blocks: 1 Center pts (total): 3

Results for: example7-1.XLS Factorial Fit: Yield versus time, temperature

Estimated Effects and Coefficients for Yield (coded units)

Term Effect Coef SE Coef T PConstant 61.8000 1.000 61.80 0.000time 4.7000 2.3500 1.000 2.35 0.143temperature 9.0000 4.5000 1.000 4.50 0.046time*temperature -1.3000 -0.6500 1.000 -0.65 0.582Ct Pt 0.5000 1.528 0.33 0.775

Factorial Design

Page 8: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Analysis of Variance for Yield (coded units)

Source DF Seq SS Adj SS Adj MS F PMain Effects 2 103.090 103.090 51.5450 12.89 0.0722-Way Interactions 1 1.690 1.690 1.6900 0.42 0.582 Curvature 1 0.429 0.429 0.4286 0.11 0.775Residual Error 2 8.000 8.000 4.0000 Pure Error 2 8.000 8.000 4.0000Total 6 113.209

Factorial Design

Page 9: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Factorial Design

Page 10: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Estimated Effects and Coefficients for Yield (coded units)

Term Effect Coef SE Coef T PConstant 62.014 0.6011 103.16 0.000time 4.700 2.350 0.7952 2.96 0.042temperature 9.000 4.500 0.7952 5.66 0.005

S = 1.59049 R-Sq = 91.06% R-Sq(adj) = 86.59%

Analysis of Variance for Yield (coded units)

Source DF Seq SS Adj SS Adj MS F PMain Effects 2 103.090 103.090 51.5450 20.38 0.008Residual Error 4 10.119 10.119 2.5296 Curvature 1 0.429 0.429 0.4286 0.13 0.740 Lack of Fit 1 1.690 1.690 1.6900 0.42 0.582 Pure Error 2 8.000 8.000 4.0000Total 6 113.209

Estimated Coefficients for Yield using data in uncoded units

Term CoefConstant -207.236time 0.470000temperature 1.80000

Factorial Design

Page 11: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Yield = 62.014 + 2.350*time +4.500*Temperature (code)time : 70 min – 80 mintemperature : 127.5℃ - 132.5℃

Deleted Residual

Perc

ent

3.01.50.0-1.5-3.0

99

90

50

10

1

Fitted Value

Del

eted

Res

idua

l

70656055

2

1

0

-1

Deleted Residual

Freq

uenc

y

2.01.51.00.50.0-0.5-1.0

3

2

1

0

Observation Order

Del

eted

Res

idua

l

7654321

2

1

0

-1

Normal Probability Plot of the Residuals Residuals Versus the Fitted Values

Histogram of the Residuals Residuals Versus the Order of the Data

Residual Plots for Yield

Factorial Design

Page 12: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Mea

n of

Yie

ld

807570

66

64

62

60

58

56132.5130.0127.5

time temperature Point TypeCornerCenter

Main Effects Plot (data means) for Yield

temperature

Mea

n

132.5130.0127.5

67.5

65.0

62.5

60.0

57.5

55.0

time

Center80 Corner

Point Type70 Corner75

Interaction Plot (data means) for Yield

Factorial Design

Page 13: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

132.5

127.58070

temperature

time

62.3

68.0

60.354.3

64.6CenterpointFactorial Point

Cube Plot (data means) for Yield

optimum condition time 80 min, temperature 132.5℃, yield = 68%

Factorial Design

Page 14: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Factorial Design

conclusion• optimum : 80 min. 132.5℃• no evidence for curvature – not arrive at no optimum value• path of steepest ascent is required

Page 15: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Method of Steepest Ascent

time

tem

pera

ture

807876747270

132

131

130

129

128

Yield

58 - 6060 - 6262 - 6464 - 6666 - 68

<

> 68

5656 - 58

Contour Plot of Yield vs temperature, time

Page 16: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

time

tem

pera

ture

1.00.50.0-0.5-1.0

1.0

0.5

0.0

-0.5

-1.0

yield

58 - 6060 - 6262 - 6464 - 6666 - 68

<

> 68

5656 - 58

Contour Plot of yield vs temperature, time

Method of Steepest Ascent

select key factor: time key factor : factor which can not be controlled easily increase of one unit (5 minutes) of key factor (time)

increase of 1.9149 temperature (4.5/2.35) *2.5 (unit of temp)

Page 17: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Method of Steepest Ascent

time positon temp position75 130.00080 134.78785 139.57490 144.36195 149.148100 153.935105 158.722110 163.509115 168.296120 173.083125 177.870

temp position

tim

e po

sito

n

180170160150140130

130

120

110

100

90

80

70

Scatterplot of time positon vs temp position

Page 18: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Method of Steepest Ascenttime positon temp position yield(S)75 130.0 62.380 134.5 73.390 144.4 86.8100 153.9 58.2

10090

yield

60

70

80

time

90

130 80140 150temp

3D Scatterplot of yield vs time vs temp

Page 19: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

current operating condition time : 90 min temperature : 145℃

22 Factorial Design around the maximum yield

22 Factorial Design

Time

Tem

pera

ture

10080140

90, 145 (3times)

150

Page 20: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

22 Factorial Design around the maximum yield

Factorial Fit: yield versus time, temp

Analysis of Variance for yield (coded units)

Source DF Seq SS Adj SS Adj MS F PMain Effects 2 23.425 23.425 11.713 5.40 0.1562-Way Interactions 1 95.062 95.062 95.062 43.81 0.022 Curvature 1 45.027 45.027 45.027 20.75 0.045Residual Error 2 4.340 4.340 2.170 Pure Error 2 4.340 4.340 2.170Total 6 167.854

Page 21: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Central Composite Design (CCD)

Stat > DOE > Modify DesignClick Add Axial Points

Page 22: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Central Composite Design (CCD)

Stat > DOE > Modify DesignClick Randomize

Page 23: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

StdOrder RunOrder CenterPt Blocks time temp yield1 2 1 1 80 140 78.82 5 1 1 100 140 84.53 4 1 1 80 150 91.24 6 1 1 100 150 77.45 3 0 1 90 145 86.86 1 0 1 90 145 87.87 7 0 1 90 145 89.7

8 12 -1 2 75.85786 145 83.3

9 9 -1 2 104.1421 145 81.2

10 10 -1 2 90 137.9289 81.2

11 14 -1 2 90 152.0711 79.5

12 8 0 2 90 145 8713 11 0 2 90 145 8614 13 0 2 90 145 89.3

Central Composite Design (CCD)

Page 24: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Central Composite Design (CCD)

Stat > DOE > Response surface > Analysis Response surfaceClick Randomize

Analysis of Variance for yield

Source DF Seq SS Adj SS Adj MS F PBlocks 1 5.406 5.406 5.406 1.75 0.228Regression 5 223.681 223.681 44.736 14.47 0.001 Linear 2 16.366 202.338 101.169 32.71 0.000 Square 2 112.253 112.253 56.126 18.15 0.002 Interaction 1 95.062 95.062 95.062 30.74 0.001Residual Error 7 21.647 21.647 3.092 Lack-of-Fit 3 11.581 11.581 3.860 1.53 0.336 Pure Error 4 10.067 10.067 2.517Total 13 250.735

Page 25: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Central Composite Design (CCD)

Remove “Blocks” from model

Analysis of Variance for yield

Source DF Seq SS Adj SS Adj MS F PBlocks 1 5.406 5.406 5.406 1.75 0.228Regression 5 223.681 223.681 44.736 14.47 0.001 Linear 2 16.366 202.338 101.169 32.71 0.000 Square 2 112.253 112.253 56.126 18.15 0.002 Interaction 1 95.062 95.062 95.062 30.74 0.001Residual Error 7 21.647 21.647 3.092 Lack-of-Fit 3 11.581 11.581 3.860 1.53 0.336 Pure Error 4 10.067 10.067 2.517Total 13 250.735

Analysis of Variance for yield

Source DF Seq SS Adj SS Adj MS F PRegression 5 223.68 223.68 44.736 13.23 0.001 Linear 2 16.37 202.34 101.169 29.92 0.000 Square 2 112.25 112.25 56.126 16.60 0.001 Interaction 1 95.06 95.06 95.062 28.11 0.001Residual Error 8 27.05 27.05 3.382 Lack-of-Fit 3 16.32 16.32 5.440 2.53 0.171 Pure Error 5 10.73 10.73 2.147Total 13 250.74

Page 26: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Central Composite Design (CCD)Estimated Regression Coefficients for yield

Term Coef SE Coef T PConstant 87.7667 0.7507 116.906 0.000time -1.3837 0.6502 -2.128 0.066temp 0.3620 0.6502 0.557 0.593time*time -2.3396 0.6767 -3.457 0.009temp*temp -3.2896 0.6767 -4.861 0.001time*temp -4.8750 0.9195 -5.302 0.001S = 1.839 R-Sq = 89.2% R-Sq(adj) = 82.5%

Estimated Regression Coefficients for yield using data in uncoded units

Term CoefConstant -4138.6980time 18.2104temp 47.0066time*time -0.0234temp*temp -0.1316time*temp -0.0975

Yield = -4139 + 18.21*time + 47.01*temp -0.0234*time+time -0.1316*temp*temp – 0.0975*time*temp

Page 27: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Central Composite Design (CCD)

Deleted Residual

Perc

ent

420-2-4

99

90

50

10

1

Fitted Value

Del

eted

Res

idua

l

90858075

4

2

0

-2

Deleted Residual

Freq

uenc

y

3210-1-2-3

4.8

3.6

2.4

1.2

0.0

Observation Order

Del

eted

Res

idua

l

1413121110987654321

4

2

0

-2

Normal Probability Plot of the Residuals Residuals Versus the Fitted Values

Histogram of the Residuals Residuals Versus the Order of the Data

Residual Plots for yield

Page 28: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Central Composite Design (CCD)

time

tem

p

10095908580

150.0

147.5

145.0

142.5

140.0

yield

77 - 8181 - 8585 - 89

> 89

< 7373 - 77

Contour Plot of yield vs temp, time

Page 29: Design and Analysis of Experiments  (7)  Response Surface Methods and Designs (2)

Central Composite Design (CCD)

152148

yield

70

80

144 temp

90

80 14090 100time

Surface Plot of yield vs temp, time