## 3 Challenges and Concept  
In order to develop a knowledge-based assistance system for process chain-oriented design evaluation of multi-stage manufactured tailored forming components, two aspects need to be considered. On the one hand, the interrelationships within a multi-stage tailored forming process chain that lead to a specific component shape must be captured and formalized in the assistance system. On the other hand, a restriction check is required which, based on the formalized process chain relationships, compares the fulfillment of requirements of all involved manufacturing steps with the specification of a tailored forming component design and derives the possible needs for the action to achieve process chain conformity. For this purpose, this paper proposes a manufacturing stage model which, starting from a predefined manufacturing process chain and a component design, derives the geometry models of the manufacturing stages required for production and simultaneously performs a restriction check. The idea of an inverse process chain representation is pursued (see Figure 2), whereby the process chain is viewed against the actual process direction. The activities required for this are shown in Figure 3. At the beginning, the user models a component and also defines a process chain with which the component is to be manufactured. The user then checks whether the component can be manufactured by the specified process chain. If this is the case, the necessary manufacturing steps can be configured. If the component cannot be manufactured, suitable measures are suggested automatically for emerging conflicts. Figure 2: Inverse process chain. The scientific goal is to support the intensive information exchange between product development and manufacturing planning by considering process chain knowledge in the component development via a knowledge-based approach, leading to a manufacturable component design. By using the holistic view of the latter process chain, the so-called process-cross manufacturing restrictions can also flow into the design department, which results from the interactions of all involved processes [11]. The challenge in formalizing process chain knowledge is the abstraction of the process steps, since the tailored forming process chain is composed of different manufacturing processes. This requires the identification of a common abstraction level so that all processes can be represented in one model. This is compounded by the data situation and the level of knowledge of tailored forming technology, the scope of which is currently still comparatively small. Therefore, the manufacturing knowledge is partly only implicitly available and the access from real test and simulation data is limited. To address these challenges, [PERSON] et al. [42] present a concept in which process knowledge is formalized in a model-based way via numerical process simulations. Thereby, the reasoning mechanism is implemented iteratively via several analysis-synthesis operations, which enables inverse process modeling and the derivation of manufacturing stages. However, this modeling of the manufacturing stage model has drawbacks. On the one hand, the modeling strategy requires a high implementation effort and results in a complex model structure. On the other hand, the iterative use of numerical simulations requires a large computing time. Furthermore, the existing approaches of the manufacturing stage model lack the aspects of how to detect possible manufacturing conflicts and how to derive measures to achieve manufacturability. In this article, the process chain is understood as a configurable design object, where sequencing (routing the component through the process chain) and parameterization (assigning process parameters) result in a process chain variant for the desired component. If both are modeled within discrete domains, the process chain can be represented as a configuration problem, which can be implemented via a Constraint Satisfaction Problem (CSP).