## 5 Application of Sys-IMF for Decision Support in Modular Product Family Design
### Phase I: Case-Specific Selection of Economical Impacts  
In a first step, the information on the company-, project- and product-specific boundary conditions is used to filter the case-specific impacts from the Sys-IMF. For this purpose, Sys-IMF is exported to MS Excel, and the effects of modularity are extracted using an implemented filter option for the stored boundary conditions (Figure 12).  
Typical input values include, e.g., type of industry, quantity, strategy or market position. However, they also project-specific parameters, such as project budget, project duration or the number of project participants, which are stored in the model and can  
Figure 11: Comparison of the component variety of the developed modular concepts and the reference concept of the medium voltage electric motors (images for visualization only).  
Figure 12: Implemented filter function for the case-specific selection of effects of modularization (here using the example of the four economic target values).  
be entered as boundary conditions. If the desired economic targets are already known, they can be selected directly at the level of the economic target values. In this way, the user can not only display case-specific effects, but also select specific savings potentials based on predefined targets. The result of this first phase is a filtered IMF, which shows the main impact chains in relation to the respective boundary conditions and targets. For the application example, a total of 22 impact chains are filtered from the model (see Figure 13).  
For visual analysis as well as for less effort handling and calculation of the KPIs, the results are generated in MS Excel. This represents a key requirement in the context of the  
Figure 13: Visual representation of the filtered IMF with the case-specific impact chains for the application example.  
practical applicability of the extended IMF. In addition, this enables interdisciplinary use of the model, which is particularly important for decision-making in the context of modular product families. In many cases, a heterogeneous team from different disciplines and with varying previous experience is involved in this early design stage in context of modularity decisions [16].  
The filtered IMF for the product family of the bearing assembly of medium-voltage electric motors in Figure 13 shows the impact chains that have already been identified in past projects under the same boundary conditions. The size of the bubbles on the right-hand side provides a qualitative measure of the potential savings (green), respectively, the expenses or disadvantages (red) of the particular effect. This information is stored in the IMF from more than 10 past modularization projects and is constantly growing. The larger the bubble, the greater the savings for this effect under similar boundary conditions. So far, these have only been included in the knowledge base qualitatively as a percentage, but in the future, they can also be partially recorded quantitatively by depositing the KPIs. Thus, using the knowledge base of the extended IMF, the impacts can not only be visualized, but also used to support the selection and evaluation of KPIs for quantification. This represents the transition to the second phase of the methodological approach to the application of the extended IMF.