# summary(lm(plan_Q46))

# Coefficients:
#                        Estimate Std. Error t value Pr(>|t|)
# (Intercept)             72.89375    0.83076  87.743 3.64e-09 ***
# Polyester1               2.88125    0.83076   3.468   0.0179 *
# CBAC1                    2.78125    0.83076   3.348   0.0204 *
# Al1                      3.11875    0.83076   3.754   0.0132 *
# Catalisador1            -1.93125    0.83076  -2.325   0.0677 .
# Polyester1:CBAC1        -1.00625    0.83076  -1.211   0.2799
# Polyester1:Al1          -0.41875    0.83076  -0.504   0.6356
# Polyester1:Catalisador1 -1.24375    0.83076  -1.497   0.1946
# CBAC1:Al1               -0.26875    0.83076  -0.323   0.7594
# CBAC1:Catalisador1       0.73125    0.83076   0.880   0.4190
# Al1:Catalisador1        -0.03125    0.83076  -0.038   0.9714

if(!require("qualityTools")) install.packages("qualityTools") ; library(qualityTools)
fat_base <- fracDesign(k = 4,
                   centerCube = 0,
                   replicates = 1)

runOrd(fat_base) <- standOrd(fat_base)

# response(fat_base) <- resp

# paretoPlot(fat_base,
       ylim = c(0,7),
       ylab = "Standadized Effects",
       xlab = "Term",
       main = "Pareto Chart of the Standadized Effects")

if(!require("FrF2")) install.packages("FrF2") ; library(FrF2)
Q14_46 <- FrF2(nfactors = 4,
           nruns = 16,
           randomize = FALSE,
           factor.names = list(
             Polyester = c(50, 70),
             CBAC = c(15, 30),
             Al = c(1, 3),
             Catalisador = c(0.25, 0.5)))

basecoat <- c(63.8, 77.6, 68.8, 76.5, 72.5, 77.2, 77.7, 84.5, 60.6, 64.9,
          72.7, 73.3, 68.0, 76.3, 76.0, 75.9)

plan_Q46 <- add.response(design = Q14_46, response = basecoat)