**5. Discussion**

All in all, it can be said that the computer-aided engineering environment has met the required expectations. On the basis of the given load cases and other boundary conditions like design space, a tailored forming high-performance part was generated. In addition, the restrictions resulting from the manufacturing processes could be fully considered. Furthermore, the CBR system provides a platform for a data-driven development of tailored forming components.

Since the tailored forming process chain is novel, basic research is conducted in CRC 1153. In order to develop controllable manufacturing processes, in the beginning, only simple, rotationally symmetric components were investigated. For these components, the most robust results have been achieved and most knowledge about manufacturing restrictions is known. For these reasons, the shaft presented in this paper is the subject of the investigations on the creation of the CAEE. However, due to the existing load cases, the full tailored forming potential cannot be developed for shafts. Therefore, mirror-symmetric geometries such as rocker arms, which offer a higher tailored forming potential, are currently being investigated in CRC 1153 (Figure 20). Nevertheless, as shown in Section 4.5, there is also tailored forming potential for shafts under certain boundary conditions and these components are therefore also suitable for the development of the CAEE.

**Figure 20.** Rocker arm (**left**) and derived tailored forming component variants in IZEO (**center**) and CAD (**right**).

Furthermore, it should be noted that all simulations have been carried out with linear-elastic material behavior up to the yield strength, since this describes the limit in which a component can be used in practice. The joining zone is designed as a simple adhesive contact. Within the scope of CRC 1153, special finite elements are being developed that can simulate the material properties of the joining zone [89]. These are currently not ye<sup>t</sup> included in the simulations described here, but will be added in the future.

In addition, test bench trials have been conducted to validate the strength of the joining zone geometries generated by IZEO and Robust Design. An optimized joining zone geometry helps the shaft to withstand higher loads. Analogy tests on simplified shafts have shown that a shaft with optimized joining zone geometry has nearly the same strength as a reference shaft made of the aluminum alloy. With a non-optimized geometry, the shaft fails in the area of the joining zone and the strength is reduced [6].

For future approaches to the development of CAEE, ontology-based approaches are probably more beneficial than the approaches presented in this paper. The ontology would serve as a mediator between the knowledge base and the instantiated CAD model. The result would be a model architecture in which e.g., the design elements could be used much more flexibly. Currently, the parameters of the design elements are hard-coded by the CAD system and are explicitly addressed so that they can practically only be used for a single or similar component.

The challenge with GPDA is that an enormous amount of work is required in advance to generate a functioning model. In order to ensure the modularity of the approach, grea<sup>t</sup> care is required in the generation of the skeleton, the interface geometries and the design elements. The creation of a model-free of errors within defined limits requires increased programming effort and a well-planned structure, especially at the beginning. Further degrees of freedom are added in the context of tailored forming by taking the joining zone into account, which must be defined both in the top-level assembly and in each design element. As shown in Figure 19a, the design elements must be controlled by the

top-level assembly so that the joining zones form a smooth transition from design element to a design element. However, the work has also shown that the effort for embedding new design elements and new joining zone geometries is reduced the more the GPDA model is built up, since they can be derived from the previously created design elements and can be integrated into the working top-level assembly relatively easily.

Furthermore, there is a significant difference in the programming effort required to implement formal, explicit and informal, implicit knowledge (see Section 2.2). While explicit knowledge can be implemented very easily, e.g., by means of table values and If-Then-Else queries, the translation effort for implicit knowledge is significantly higher and also ties up more computing capacity. However, as IZEO has shown, implementation is quite possible. In summary, it can be said that computer-aided methods can handle explicit knowledge very well, but there is still a need for research on the implementation of implicit knowledge.

#### **6. Summary and Outlook**

The desire for components that are always better adapted to external conditions than their predecessors leads to the technological advancement of the components, but also of the processes required for their manufacture. As a result, components and processes are becoming more and more complicated, so that the effort for planning, conception, design and elaboration is increasing. In some cases, components and process chains are already so complicated that the optimal solution is no longer readily apparent. When newer approaches, such as multi-material design, are added, the degrees of freedom to be considered increase even further. Especially in this case, systematic, computer-aided approaches are needed to meet the challenge of finding the best solution from an objective point of view. Therefore, modeling approaches and design methods are needed that take into account the manufacturing processes throughout the entire product development process.

The methodology presented in this work works as a framework to develop the technology of tailored forming further and generate continuously better solutions. As seen, the topology optimization method IZEO was able to handle dynamic manufacturing restrictions while optimizing the use of multi-materials. Additionally, different strategies for solution exploration were presented, such as CBR and GPDA, where the influence of manufacturing is direct. For these reasons, this design methodology is able to support this manufacturing technology to be further developed. This translates into first transfer projects for real industry applications that are being currently performed under the umbrella of the CRC 1153.

All in all, computer-aided engineering environments help to find the optimum shape for a component in order to derive the best possible manufacturing process. The stored knowledge base provides a clear and objective set of rules that can protect companies from undesirable developments. This provides a better starting point for the development of components and processes. Routine processes can also be automated, giving designers more room for creative work.

In further developments, additional non-rotationally symmetric components will be investigated and developed. For this purpose, complicated manufacturing restrictions have to be implemented for IZEO. The GPDA also needs skeletons and design elements with more complicated shapes and extended functionalities. For example, the skeleton will no longer be one-dimensional, but two or three dimensional. The design elements may have more than two neighboring elements. In order to better link product development with process development in the future, a transfer model is currently being worked on within the framework of CRC 1153, which will allow conclusions to be drawn about the upstream production stages. For this purpose, a GPDA model is currently being developed, which, depending on the manufacturing process, can map the individual stages of component production. In this case, the research results from the CRC will also serve as a basis.

**Author Contributions:** Conceptualization, R.S. and T.B.; methodology, R.S. and T.B.; software, R.S. and T.B.; validation, R.S., T.B. and P.C.G.; formal analysis, R.S. and T.B.; investigation, R.S. and T.B.; resources, R.L.; data curation, R.L.; writing—original draft preparation, R.S., T.B. and P.C.G.; writing—review and editing, T.B. and P.C.G.; visualization, R.S. and T.B.; supervision, P.C.G., I.M. and R.L.; project administration, P.C.G., I.M. and R.L.; funding acquisition, I.M. and R.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) gran<sup>t</sup> number 252662854.

**Acknowledgments:** The results presented in this paper were obtained within the subproject C2 "Configuration and design of hybrid solids" of the Collaborative Research Center 1153 "Process chain to produce hybrid high performance components by Tailored Forming". The authors would like to thank the German Research Foundation (DFG) for the financial and organizational support of this project.

**Conflicts of Interest:** The authors declare no conflict of interest.
