## 6 Industrial Application of the Developed Approach
### Application of Step 2: Solution Space Planning and Control
model of the _Level_1_ customer-supplier relationship between the _rotor_, the _stator_, the _housing_, and the _electric motor_ assembly lines is considered (_SC07_). This results in two alternative operating models being considered for the industrial application. To meet the network-operations-based requirements (_O-RQ1-O-RQ3_) from Table 2, the network capacity must be equal to the fixed demand volume on a weekly basis. Therefore, product mix alternatives must be included to derive capacity framework alternatives. Thus, the take rate for each product and the BOM of the product are used to generate product mix alternatives. Capacity framework alternatives are now generated by combining the variant strategy decision alternatives, the operating model decision alternatives, and the product mix alternatives. This results in four capacity framework alternatives being considered for the industrial application. The statistical production line characteristics can be varied based on the production line failures, as shown in Figure 11a. In strategic network design, many production line characteristics are uncertain. Therefore, production line failures can be estimated based on similar existing production lines using aggregated line models, as presented in [46; 47]. For this industrial application, only the production line behavior of the _rotor_ lines is varied between a worst-case and a realistic case (_SC04_). Considering the different numbers of _rotor_ lines for each network structure alternative, this leads to a total of eight production line behavior alternatives for this industrial application. Logistics information alternatives are generated based on the applied initial and maximum inventory levels for each warehouse; see Figure 11b. According to _SC07_, there is a warehouse in between each _Level_1_ customer-supplier relationship. To create the alternatives, sampling experiment design methods such as the NOLH design [34] could also be applied. For this industrial application, three warehouses are considered within the production network (_rotor_, _stator_, and _housing_). For each warehouse, two different inventory levels are applied (_SC08_). This leads to a total of eight logistics information alternatives for this industrial application. A summary of the number of alternative solutions for each sub-solution space is presented in Table 3. All alternative solutions are multiplied to create the final experiment design. For this industrial application, the procedure leads to 1024 alternative solutions. The final experiment design is then used to generate simulation software-specific input data sets by a post-processing Python script. The final step of solution space control is completely different from the corresponding step in the product development context, c. f. Section 2.3. This is because there is no strict shortage of necessary resources to develop all alternative solutions. Each simulation run of the experiment design is executed, and the alternative solution is developed in a way that the simulation results can be used to evaluate the alternative solution. Thereby, the only consumed resource is computing power and data storage capacity. Figure 11: (**a**) Procedure to derive production line behavior alternatives; (**b**) procedure to derive logistics information alternatives.