## 4 Experiments, Results, and Discussion
### Production of the Scraper Conveyor Chute
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Operation**} & \multicolumn{2}{c}{**Processing Times**} & \multicolumn{2}{c}{**Resources**} \\  & **Min** & **Max** & **Employees (Person)** & **Tools (pes)** \\ \hline Assembly 1 & 120.0 & 150.0 & 3 assemblers & 2 assembly stations \\ Welding 1 & 360.0 & 425.0 & 6 welders & 3 welding aggregates \\ Assembly 2 & 240.0 & 270.0 & 3 assemblers & 2 assembly stations \\ Welding 2 & 510.0 & 606.3 & 6 welders & 3 welding aggregates \\ Grinding & 180.0 & 210.0 & 3 grinders & 3 grinding stations \\ \hline
**Sum** & **1410.0** & **1661.3** & **-** & **-** \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Processing times of individual operations of the technological process of producing the scraper conveyor chute. Figure 6: Progress in minimizing the time completion criterion for the scraper conveyor chute production process  
In iteration 2 for scheduling, order 2 was drawn. Furthermore, in the order selecting step, the probability of drawing any order is the same. In the case of order 2, the _Assembly 2_ operation was selected. During the selection of resources for this operation, the nondeterministic nature of the algorithm is again visible. The _Assembly station 2_ tool was assigned to the operation, although the assignment of a different tool could ensure faster execution of the order. However, thanks to this, a full search of the solution space is again ensured. In iteration 4, the operation _Welding 1_ was inserted for order 3. Despite the prior availability of the allocated production resources, it starts at 9.30 a.m. because the component in Equation (1) of the feasibility constraint must be met. Note that the assembly operation inserted into iteration 5 takes longer than the corresponding operation inserted into iteration 1. The influence of the employee (assembler) is revealed here. The final operation of order 3--_Grinding_--can be inserted into iteration 10 according to the feasibility constraint component only after both welding operations have been completed. Importantly, the algorithm placed the grinding immediately after welding to make the schedule as compact as possible. In the orders' section for the presented freeze state of the algorithm execution, operations already inserted into the schedule are marked with a thicker edge. In the presented state, some operations still need to be inserted. After inserting all operations, loop \(A\) ends, the criterion is assessed (cost or execution time), the schedule is cleared, and the next iteration of the master loop \(B\) begins. The example presented above was a simplified visualization of the algorithm's work for the proposed dynamic methodology. The actual experiments compared the efficiency for a representative production volume of the standard methodology (neglecting the impact of  
Figure 7: Example production schedule generation process for the scraper conveyor chute. the allocation of production resources) with the new methodology developed. The results of the first experiment on increasing productivity are shown in the form of a green graph in Figure 8. By analyzing these results, it can be concluded that the profit \(\Phi_{max}\) for the maximum completion time measure (understood as a relative decrease in this value defined in Equation (8)) is independent of the number of scheduled orders and oscillates between \(11+12\%\). The main reason for such a significant reduction in the execution time of a production plan after applying the new methodology to production scheduling is the assumption of constant times for the implementation of individual technological operations in the standard methodology. In industrial practice, these times are set at a safe level, ensuring the correct execution of the task even by the worst variant of the assigned combination of production resources. Assuming a shorter time than the maximum (e.g., average) time may result in a too short execution time being planned for some production resources.