## 2 Methodology  
The layer-by-layer build-up of material in SLM can lead to the formation of three near-surface areas with different material properties depending on the part shape to be manufactured. As a result, there is a direct interrelation between product design and manufacturing in the product development process for SLM parts given the investigated process parameters. In order to generate a design adapted to SLM which cannot be considered intuitive due to the interrelation, computer-aided optimization methods are suitable. Therefore, these optimization methods must be adapted in order to handle the basic parameters (e.g., material properties or print direction). As shown previously, thus far, no topology optimization approach exists which takes into account three porous material areas along a given print direction. Therefore, an optimization method has been developed which iteratively considers these three areas to generate a new product design [17; 22]. This contribution refers to the further development of the 3D optimization method. Due to the good availability and high robustness of commercial tools, the optimization method was developed based on Abaqus 2019 as well as Tosca 2019 and uses their solvers [23]. The basic procedure of the developed optimization method is characterized by the interruption of the topology optimization in each iteration. Then, based on the interim result obtained from the interruption, the three porous areas including the associated material properties of the SLM are determined and adopted as input parameters for further calculation in the next iteration. The procedure is repeated until a convergence criterion is reached. This creates a possibility to integrate the restrictions of the investigated SLM in a sensitivity-based topology optimization. The aim is to achieve an improved product design in terms of stiffness through the targeted, iterative manipulation of the topology optimization in comparison to a standardized topology optimization. Based on this, the method will be extended in the future to consider the maximum permissible stress in the three areas. This will be conducted by adding a global strength constraint, thus creating an advantage compared to a standard topology optimization. The workflow of the developed optimization method is shown in Figure 2. It will be explained in the following and, at the same time, serves to structure this contribution. In the first step, _Part Geometry_, a part is defined that will be used in the optimization method. For this purpose, the part is derived from any CAD software, such as Creo Parametrics 4, and imported into a FE software such as Abaqus 2019. In the step _Initial FE model_, the load case including boundary conditions as well as the initial FE mesh (mesh type and size) for the topology optimization is specified and the optimization parameters are defined in the FE software. Furthermore, in this step, the material properties from the hatching area are applied to the entire part. Therefore, no differentiation into the three areas is made at this point. With this initial FE model, a sensitivity-based topology optimization is started in Tosca Structure 2019. Within this optimization, the sensitivities are calculated in Abaqus [24] and are adjusted by the MMA algorithm according to [5]. In the further progress of the method, the material properties are adapted to the material properties in the contour and interface area by manipulating the fictive densities (see step _Density distribution_). In each iteration, the topology optimization is now interrupted right before the solver is started. During this interruption, the steps _Determination of the material areas_, _Material assignment_, _Transfer of data_ and _Density distribution_ are performed and represent the core of the developed optimization method. By these four steps, the three porous areas are determined, and the associated material properties are defined and passed to the topology optimization as input to calculate the next iteration.