Load Data File and Print the Summary
Data <- read_csv("C:/Users/insul/Desktop/New_Test/Data.csv")
Data=Data[,-1] # Remove 1st Colum Containing the Experiment Number
## Print Data Head
head(Data)
## # A tibble: 6 x 5
## PA DC EC RR ST
## <int> <int> <int> <int> <dbl>
## 1 19 60000 60000 10 9.964230
## 2 19 60000 60000 11 9.978677
## 3 19 60000 60000 12 9.993216
## 4 19 60000 70000 10 9.275423
## 5 19 60000 70000 11 11.690901
## 6 19 60000 70000 12 12.022495
## Summary of the Data
summary(Data)
## PA DC EC RR
## Min. :19.0 Min. :60000 Min. :60000 Min. :10
## 1st Qu.:19.0 1st Qu.:60000 1st Qu.:60000 1st Qu.:10
## Median :19.5 Median :70000 Median :70000 Median :11
## Mean :19.5 Mean :70000 Mean :70000 Mean :11
## 3rd Qu.:20.0 3rd Qu.:80000 3rd Qu.:80000 3rd Qu.:12
## Max. :20.0 Max. :80000 Max. :80000 Max. :12
## ST
## Min. : 8.474
## 1st Qu.: 8.958
## Median : 9.446
## Mean : 9.668
## 3rd Qu.: 9.976
## Max. :12.082
Creating the Taguchi Experiment
## Creating Taguchi Orthogonal Array
SettlingTimeArray = oa.design(factor.names=c("PA", "DC", "EC","RR"), nlevels=c(2,3,3,3), columns="min3")
SettlingTimeArray
## PA DC EC RR
## 1 1 2 1 3
## 2 2 2 1 2
## 3 1 3 2 1
## 4 2 3 2 3
## 5 2 2 2 1
## 6 1 1 1 1
## 7 2 3 3 2
## 8 2 1 1 3
## 9 2 3 1 1
## 10 1 2 3 1
## 11 1 3 1 2
## 12 1 2 2 2
## 13 1 3 3 3
## 14 1 1 3 2
## 15 2 2 3 3
## 16 2 1 3 1
## 17 2 1 2 2
## 18 1 1 2 3
## class=design, type= oa
## Getting the Responses for the Taguchi Experiments
dataarray = merge(SettlingTimeArray, DataSub, by=c("PA", "DC", "EC","RR"), all=FALSE)
head(dataarray)
## PA DC EC RR ST
## 1 1 1 1 1 9.964230
## 2 1 1 2 3 12.022495
## 3 1 1 3 2 11.367710
## 4 1 2 1 3 9.846146
## 5 1 2 2 2 9.169872
## 6 1 2 3 1 8.617264
S/N Ratio
# SN Ratio
SN=-10*log10(1/dataarray$ST^2)
# We find that our best solution is the one with the highest signal to noise ratio.
bestsn = which(SN==max(SN))
print(paste('Signal to Noise Ratio:',bestsn))
## [1] "Signal to Noise Ratio: 2"
Fitting the model for Taguchi Design
# Taguchi Level Run
TaguchiModel = lm(ST~. +PA*DC+ PA*EC +PA*RR + DC*EC +DC*DC,data = dataarray)
TaguchiModel.step <- stepAIC(TaguchiModel,trace = TRUE)
## Start: AIC=-112.14
## ST ~ PA + DC + EC + RR + PA * DC + PA * EC + PA * RR + DC * EC +
## DC * DC
##
##
## Step: AIC=-112.14
## ST ~ PA + DC + EC + RR + PA:DC + PA:EC + DC:EC
##
## Df Sum of Sq RSS AIC
## - PA:EC 2 0.0009 0.0069 -113.631
## <none> 0.0060 -112.136
## - PA:DC 2 0.0111 0.0170 -97.318
## - RR 2 0.0170 0.0230 -91.914
## - DC:EC 4 4.7388 4.7448 0.000
##
## Step: AIC=-113.63
## ST ~ PA + DC + EC + RR + PA:DC + DC:EC
##
## Df Sum of Sq RSS AIC
## <none> 0.0069 -113.631
## - PA:DC 2 0.0111 0.0179 -100.398
## - RR 2 0.0170 0.0239 -95.228
## - DC:EC 4 4.7388 4.7457 -3.996
# Anova Results
anova(TaguchiModel.step)
## Analysis of Variance Table
##
## Response: ST
## Df Sum Sq Mean Sq F value Pr(>F)
## PA 1 0.0053 0.0053 3.0670 0.1548
## DC 2 15.5754 7.7877 4522.6517 1.954e-07 ***
## EC 2 0.8553 0.4277 248.3586 6.382e-05 ***
## RR 2 0.6983 0.3491 202.7581 9.541e-05 ***
## PA:DC 2 0.0111 0.0055 3.2099 0.1474
## DC:EC 4 4.7388 1.1847 688.0085 6.313e-06 ***
## Residuals 4 0.0069 0.0017
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# Model Estimates
summary(TaguchiModel.step)
##
## Call:
## lm.default(formula = ST ~ PA + DC + EC + RR + PA:DC + DC:EC,
## data = dataarray)
##
## Residuals:
## 1 2 3 4 5 6
## -0.0256552 0.0335856 -0.0079304 -0.0177990 -0.0084470 0.0262460
## 7 8 9 10 11 12
## 0.0163774 -0.0005908 -0.0157866 0.0256552 -0.0335856 0.0079304
## 13 14 15 16 17 18
## 0.0177990 0.0084470 -0.0262460 -0.0163774 0.0005908 0.0157866
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.756418 0.009781 997.514 6.06e-12 ***
## PA1 -0.017129 0.009781 -1.751 0.154785
## DC.L -1.464938 0.016941 -86.474 1.07e-07 ***
## DC.Q 0.670711 0.016941 39.592 2.43e-06 ***
## EC.L -0.197306 0.016941 -11.647 0.000311 ***
## EC.Q -0.321904 0.016941 -19.002 4.52e-05 ***
## RR.L 0.060194 0.019561 3.077 0.037033 *
## RR.Q 0.012638 0.019561 0.646 0.553444
## PA1:DC.L 0.038896 0.016941 2.296 0.083302 .
## PA1:DC.Q -0.018151 0.016941 -1.071 0.344322
## DC.L:EC.L -1.183319 0.031693 -37.337 3.07e-06 ***
## DC.Q:EC.L 0.787014 0.031693 24.832 1.56e-05 ***
## DC.L:EC.Q 0.723240 0.031693 22.820 2.18e-05 ***
## DC.Q:EC.Q -0.427935 0.031693 -13.502 0.000174 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0415 on 4 degrees of freedom
## Multiple R-squared: 0.9997, Adjusted R-squared: 0.9987
## F-statistic: 977.6 on 13 and 4 DF, p-value: 2.41e-06
Residual Plots
par(mfrow=c(1,2))
# QQ plots for residuals of second model
qqnorm(residuals(TaguchiModel.step))
qqline(residuals(TaguchiModel.step))
# Residual Plot
plot(fitted(TaguchiModel.step), residuals(TaguchiModel.step))
![](data:image/png;base64,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)
Fitting the model for Full Factorial Design
FullFact = lm(ST~. +PA*DC+ PA*EC +PA*RR + DC*EC +DC*DC,data = DataSub)
FullFact.step <- stepAIC(FullFact,trace = TRUE)
## Start: AIC=-41.17
## ST ~ PA + DC + EC + RR + PA * DC + PA * EC + PA * RR + DC * EC +
## DC * DC
##
## Df Sum of Sq RSS AIC
## - PA:EC 1 0.0001 18.051 -43.172
## - PA:RR 1 0.0001 18.051 -43.172
## - PA:DC 1 0.0009 18.052 -43.169
## <none> 18.051 -41.172
## - DC:EC 1 8.7748 26.826 -21.779
##
## Step: AIC=-43.17
## ST ~ PA + DC + EC + RR + PA:DC + PA:RR + DC:EC
##
## Df Sum of Sq RSS AIC
## - PA:RR 1 0.0001 18.051 -45.171
## - PA:DC 1 0.0009 18.052 -45.169
## <none> 18.051 -43.172
## - DC:EC 1 8.7748 26.826 -23.779
##
## Step: AIC=-45.17
## ST ~ PA + DC + EC + RR + PA:DC + DC:EC
##
## Df Sum of Sq RSS AIC
## - PA:DC 1 0.0009 18.052 -47.169
## <none> 18.051 -45.171
## - RR 1 1.3740 19.425 -43.210
## - DC:EC 1 8.7748 26.826 -25.779
##
## Step: AIC=-47.17
## ST ~ PA + DC + EC + RR + DC:EC
##
## Df Sum of Sq RSS AIC
## - PA 1 0.0034 18.056 -49.159
## <none> 18.052 -47.169
## - RR 1 1.3740 19.426 -45.207
## - DC:EC 1 8.7748 26.827 -27.777
##
## Step: AIC=-49.16
## ST ~ DC + EC + RR + DC:EC
##
## Df Sum of Sq RSS AIC
## <none> 18.056 -49.159
## - RR 1 1.3740 19.430 -47.198
## - DC:EC 1 8.7748 26.830 -29.770
# Anova Results
anova(FullFact.step)
## Analysis of Variance Table
##
## Response: ST
## Df Sum Sq Mean Sq F value Pr(>F)
## DC 1 28.9468 28.9468 78.5571 9.436e-12 ***
## EC 1 0.6353 0.6353 1.7240 0.19529
## RR 1 1.3740 1.3740 3.7289 0.05927 .
## DC:EC 1 8.7748 8.7748 23.8135 1.166e-05 ***
## Residuals 49 18.0556 0.3685
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# Model Estimates
summary(FullFact.step)
##
## Call:
## lm.default(formula = ST ~ DC + EC + RR + DC:EC, data = DataSub)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.09413 -0.31215 0.06153 0.32728 1.32144
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.9179 0.6126 14.557 < 2e-16 ***
## DC 0.3126 0.2677 1.168 0.248487
## EC 1.0765 0.2677 4.022 0.000199 ***
## RR 0.1954 0.1012 1.931 0.059275 .
## DC:EC -0.6047 0.1239 -4.880 1.17e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.607 on 49 degrees of freedom
## Multiple R-squared: 0.6875, Adjusted R-squared: 0.662
## F-statistic: 26.96 on 4 and 49 DF, p-value: 7.477e-12
Optimum Values (Using Taguchi Array)
## Convert to Numeric from factor
dataarray$PA=as.numeric(dataarray$PA)
dataarray$DC=as.numeric(dataarray$DC)
dataarray$EC=as.numeric(dataarray$EC)
dataarray$RR=as.numeric(dataarray$RR)
dataarray$ST=as.numeric(dataarray$ST)
## Plot the Response Surface
par(mfrow=c(2,3))
Response_Surface=rsm(ST~FO(PA,DC,EC,RR)+TWI(DC,EC),data = dataarray)
contour(Response_Surface,~PA+DC+EC+RR+DC*EC,image=TRUE,color.palette = cm.colors)
![](data:image/png;base64,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)
Optimum Values (Using all 54 Runs)
## Plot the Response Surface
par(mfrow=c(2,3))
Response_Surface=rsm(ST~FO(PA,DC,EC,RR)+TWI(DC,EC),data = DataSub)
contour(Response_Surface,~PA+DC+EC+RR+DC*EC,image=TRUE,color.palette = cm.colors)
![](data:image/png;base64,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)
Checking Back With Box-Plot (Using All the 54 Runs)
DataUse=Data
# Converting them into Factor Variables
DataUse$PA <- as.factor(DataUse$PA)
DataUse$DC <- as.factor(DataUse$DC)
DataUse$EC <- as.factor(DataUse$EC)
DataUse$RR <- as.factor(DataUse$RR)
# Box-Plot for Data Distribution
par(mfrow=c(2,2))
boxplot(ST~PA,data=DataUse, xlab="Pitch Angle", ylab="Settling Time")
boxplot(ST~DC ,data=DataUse, xlab="Damping Co-efficient", ylab="Settling Time")
boxplot(ST~EC,data=DataUse, xlab="Elastic Co-efficient", ylab="Settling Time")
boxplot(ST~RR,data=DataUse, xlab="Rotor Radius", ylab="Settling Time")
![](data:image/png;base64,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)