## 4 Results
### RT Models as a Precursor for Response Surface Methods
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multicolumn{2}{c}{**Tensile Strength (kPa) Quantiles**} & \multicolumn{2}{c}{**Face Plate Position (mm) Quantiles**} & \multicolumn{2}{c}{**Core Dust Speed (m/min) Quantiles**} \\
100.0\% maximum & 1275.575 & 100.0\% maximum & 10.459 & 100.0\% maximum & 24.542 \\
99.5\% & 1226.483 & 99.5\% & & 10.456 & 99.5\% & 24.195 \\
97.5\% & 1137.675 & 97.5\% & & 10.422 & 97.5\% & 22.788 \\
90.0\% & 1067.346 & 90.0\% & & 9.720 & 90.0\% & 19.928 \\
75.0\% quartile & 1020.46 & 75.0\% quartile & 9.140 & 75.0\% quartile & quartile & 16.468 \\
50.0\% median & 951.51 & 50.0\% median & 8.324 & 50.0\% median & 10.921 \\
25.0\% quartile & 882.56 & 25.0\% quartile & 5.492 & 25.0\% quartile & quartile & 8.245 \\
10.0\% & 827.4 & 10.0\% & & 4.160 & 10.0\% & 7.094 \\
2.5\% & 767.4135 & 2.5\% & & 3.135 & 2.5\% & 6.128 \\
0.5\% & 704.1174 & 0.5\% & & 2.271 & 0.5\% & 3.539 \\
0.0\% minimum & 668.815 & 0.0\% minimum & 2.180 & 0.0\% minimum & 2.851 \\
**Summary Statistics** & & **Summary Statistics** & & **Summary Statistics** & \\  & Mean & 950.0881 & Mean & 0.321 & Mean & 41.069 \\ Std Dev & 94.6977 & Std Dev & 0.068 & Std Dev & 16.341 \\ Std Err Mean & 3.831056 & Std Err Mean & 0.003 & Std Err Mean & 0.772 \\ Upper 95\% Mean & 957.618 & Upper 95\% Mean & 0.327 & Upper 95\% Mean & 42.587 \\ Lower 95\% Mean & 942.5644 & Lower 95\% Mean & 0.315 & Lower 95\% Mean & 39.552 \\ N & 408 & N & 408 & N & 408 \\
**Quantiles** & & **Face Steam Flow (bar) Quantiles** & **Adhesive Percent (\%) Quantiles** \\
100.0\% & 100.0\% & 100.0\% & 100.0\% maximum & 292.618 & 100.0\% maximum & 14.743 \\
99.5\% & 99.5\% & 99.5\% & 99.5\% & 285.132 & 99.5\% & 14.583 \\
97.5\% & 97.5\% & 97.5\% & 97.5\% & 231.635 & 97.5\% & 14.089 \\
90.0\% & 90.0\% & 90.0\% & 90.0\% & 190.579 & 90.0\% & 13.687 \\
75.0\% & 75.0\% & 75.0\% & 75.0\% quartile & 160.880 & 75.0\% quartile & quartile & 9.555 \\
50.0\% & 50.0\% & 50.0\% & 50.0\% median & 114.143 & 50.0\% median & 9.468 \\
25.0\% & 25.0\% & 25.0\% & 25.0\% quartile & 69.911 & 25.0\% quartile & quartile & 8.579 \\
10.0\% & 10.0\% & 10.0\% & 10.0\% & 60.558 & 10.0\% & 7.662 \\
2.5\% & 2.5\% & 2.5\% & 2.5\% & 51.778 & 2.5\% & 5.985 \\
0.5\% & 0.5\% & 0.5\% & 0.5\% & 49.570 & 0.5\% & 5.679 \\
0.0\% & 0.0\% & 0.0\% & 0.0\% minimum & 48.733 & 0.0\% minimum & 5.671 \\ \multicolumn{2}{c}{**Summary Statistics**} & \multicolumn{2}{c}{**Summary Statistics**} & \multicolumn{2}{c}{**Summary Statistics**} \\ \multicolumn{2}{c}{Mean} & \multicolumn{2}{c}{Mean} & \multicolumn{2}{c}{Mean} & \multicolumn{2}{c}{121.76} & \multicolumn{2}{c}{Mean} & \multicolumn{2}{c}{9.50} \\ Std Dev & Std Dev & Std Dev & 53.10 & Std Dev & 1.93 \\ Std Err Mean & Std Err Mean & 2.36 & Std Err Mean & 0.09 \\ Upper 95\% Mean & Upper 95\% Mean & Upper 95\% Mean & 126.39 & Upper 95\% Mean & 9.68 \\ Lower 95\% Mean & Lower 95\% Mean & Lower 95\% Mean & 117.13 & Lower 95\% Mean & 9.31 \\ N & 408 & N & 408 & N & 408 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Descriptive statistics for the dependent and independent variables in the regression tree (RT) model for MDF. Designs for OSB from the RT model. Given that the OSB RT model resulted in three significant factors, A = 'dryer inlet temperature', B ='mat weight', and C = 'wet bin speed' at an \(\alpha=0.05\), a full factorial design is feasible, e.g., 2\({}^{k}\), \(k=3\), \(n=16\) with a power of 84% for significant main effects (assuming an \(\alpha=0.05\) for the experiment) (see Table 6 and Figure 2). Even though this design has no aliasing assumptions, it only explores corner points. A Box-Behnken RSM design would require two fewer runs, \(n=15\), with three center points (Figure 3). An alternative design would be a spherical circumscribed CCD RSM design with \(n=17\), \(k=3\), with four axial points (Figure 3), where the run order is presented in Table 7. Even though there are many other feasible designs, the aforementioned designs were developed to minimize the number of experimental runs while using the helpful results of the RT models.