**5. Applications in manufacturing management – results discussion**

The simulation can generate data for all processes, individually. For instance, Figure 5 shows the results in place INPUT Sewing Process – m44, the operator at this place is overloaded, also observed in the real process. An alternative would be a redistribution of tasks, adopting parallelisms, without overloading the following posts.

A different situation is shown in Figure 6, the time that the operator is idle in this place is low, and there are no accumulations of tasks over time. This represents that, for this place, the tasks are well distributed.

Other screens allow similar analyzes in all manufacturing places. It is important to analyze the changes in the manufacturing and the impacts that an action causes in each process (for instance, allocate more operators to develop a specific task).

**Figure 7.** Presents the complete Petri Net model in shoes manufacturing.

**Figure 5.** Place: "INPUT Sewing Process – m44"– Results obtained with the simulation

**Figure 6.** Place: Eyelets verification – m59– Results obtained with the simulation

**Figure 7.** Presents the complete Petri Net model in shoes manufacturing.

102 Petri Nets – Manufacturing and Computer Science

**Figure 5.** Place: "INPUT Sewing Process – m44"– Results obtained with the simulation

**Figure 6.** Place: Eyelets verification – m59– Results obtained with the simulation
