# Simulation on Cooperative Changeover of Production Team Using Hybrid Modeling Method
## Case Study
### Results and Discussion
#### 5.3.3 General Discussion  
The two sections above provide management advice for production systems that focus on a single indicator. For production systems that focus on the above two indicators, when only mature products can be produced, both the totally cooperative strategy and the non-cooperative strategy are satisfactory strategies. On the other hand, when new products are introduced in small quantities, the three strategies, except the cooperative strategy for mature products, are all satisfactory strategies. However, when new products are introduced in medium or large quantities, the totally cooperative strategy is the optimal one among the four strategies. The experimental results show that the effectiveness of cooperative changeover is indeed related to the degree of cooperation and the new products introduction rate. According to the results of this \begin{table}
\begin{tabular}{c c c c c} \hline
**Null Hypothesis** & **Degree of Freedom** & **T value /Significance** & **Test Result** & **Test Conclusion** \\ \hline \(\overline{T_{0}^{1}}=\overline{T_{0}^{4}}\) & 38 & \(-\)3.30 *** & Rejection & \(\overline{T_{0}^{1}}<\overline{T_{0}^{4}}\) \\ \(\overline{T_{25\%}^{1}}=\overline{T_{25\%}^{2}}\) & 38 & \(-\)1.18 & No rejection & Uncertain \\ \(\overline{T_{25\%}^{1}}=\overline{T_{25\%}^{3}}\) & 37.34 & 1.70 * & Rejection & \(\overline{T_{25\%}^{1}}>\overline{T_{25\%}^{3}}\) \\ \(\overline{T_{25\%}^{1}}=\overline{T_{25\%}^{3}}\) & 38 & \(-\)2.03 ** & Rejection & \(\overline{T_{25\%}^{1}}<\overline{T_{25\%}^{4}}\) \\ \(\overline{T_{25\%}^{2}}=\overline{T_{25\%}^{3}}\) & 38 & 2.26 ** & Rejection & \(\overline{T_{25\%}^{1}}>\overline{T_{25\%}^{3}}\) \\ \(\overline{T_{25\%}^{2}}=\overline{T_{25\%}^{4}}\) & 36.97 & \(-\)0.84 & No rejection & Uncertain \\ \(\overline{T_{25\%}^{3}}=\overline{T_{25\%}^{4}}\) & 38 & \(-\)2.98 *** & Rejection & \(\overline{T_{25\%}^{3}}<\overline{T_{25\%}^{4}}\) \\ \(\overline{T_{25\%}^{1}}=\overline{T_{25\%}^{2}}\) & 35.40 & 0.68 & No rejection & Uncertain \\ \(\overline{T_{25\%}^{1}}=\overline{T_{25\%}^{3}}\) & 38 & 4.09 *** & Rejection & \(\overline{T_{25\%}^{1}}>\overline{T_{25\%}^{3}}\) \\ \(\overline{T_{25\%}^{1}}=\overline{T_{25\%}^{4}}\) & 35.78 & 2.18 ** & Rejection & \(\overline{T_{25\%}^{1}}>\overline{T_{25\%}^{4}}\) \\ \(\overline{T_{25\%}^{2}}=\overline{T_{25\%}^{3}}\) & 38 & 2.59 ** & Rejection & \(\overline{T_{25\%}^{2}}>\overline{T_{25\%}^{3}}\) \\ \(\overline{T_{25\%}^{2}}=\overline{T_{25\%}^{4}}\) & 37.98 & 1.32 & No rejection & Uncertain \\ \(\overline{T_{25\%}^{3}}=\overline{T_{25\%}^{4}}\) & 38 & \(-\)0.98 & No rejection & Uncertain \\ \(\overline{T_{25\%}^{1}}=\overline{T_{25\%}^{2}}\) & 35.64 & 0.90 & No rejection & Uncertain \\ \(\overline{T_{25\%}^{1}}=\overline{T_{25\%}^{3}}\) & 36.82 & 3.95 *** & Rejection & \(\overline{T_{25\%}^{1}}>\overline{T_{25\%}^{3}}\) \\ \(\overline{T_{25\%}^{1}}=\overline{T_{25\%}^{4}}\) & 35.78 & 2.42 ** & Rejection & \(\overline{T_{25\%}^{1}}>\overline{T_{25\%}^{4}}\) \\ \(\overline{T_{25\%}^{2}}=\overline{T_{25\%}^{3}}\) & 37.75 & 3.53 *** & Rejection & \(\overline{T_{25\%}^{2}}>\overline{T_{25\%}^{3}}\) \\ \(\overline{T_{25\%}^{2}}=\overline{T_{25\%}^{4}}\) & 30.98 & 1.88 * & Rejection & \(\overline{T_{25\%}^{2}}>\overline{T_{25\%}^{4}}\) \\ \(\overline{T_{25\%}^{3}}=\overline{T_{25\%}^{4}}\) & 32.53 & \(-\)0.77 & No rejection & Uncertain \\ \hline \end{tabular} Note. * means \(p<0.1\), ** means \(p<0.05\), *** means \(p<0.01\).  
\end{table} 
Table 9: Hypothesis test results. study, the managers of production systems can choose the optimal or satisfactory cooperative strategy according to the production scenario and their objectives. At present, the research on cooperative behavior of operators in production systems mainly adopts mathematical programming, optimization approaches, single discrete-event simulation, or single agent-based simulation.