## 4 Discussion  
The discussion focuses on the suitability of given topology optimization for anisotropic materials, given a pre-requisite understanding of the CF4 and its limitations. Therefore, the following discussion does not exhaustively address CF4 and its differences in adopting a particular TO method. Thus, the focus is on investigating the suitability of TO strategies that can fully exploit the design freedom offered by CF4 technologies. As mentioned earlier in Section 3, the existing techniques for material orientation are categorized into five major classes: continuous, discrete, discrete-continuous, feature, and material parameterization. Optimizing a prescribed set of alternative discrete angles, referred to as the DMO, is often preferred in the aerospace, automotive, and wind turbine industries for manufacturability reasons. The DMO approach is favorable for multi-layer composite laminate designs [134; 135; 136] because a mixed-integer programming problem is formulated as a continuous problem that can be solved efficiently using gradient-based optimizers. As a result, substantial problems that might not be amenable to gradient-free methods can use DMO parameterization. Given the simplicity of DMO and the possibility of attaining the discrete setting for material orientation, it attracted various industrial applications with the flexibility to embrace different manufacturing units available in the market. However, restrictive DMO measures on material orientation design space may only partially exploit the potential of CF4, and the deduction is based on limited literature on its applicability to CF4. Alternatively, optimization of the multi-layered composite laminates [137] can be attacked using an indirect approach, i.e., by applying lamination parameters, as introduced by [PERSON] and [PERSON] [138]. It parameterized composite laminate's stiffness utilizing twelve linearly interdependent parameters. Therefore, it is advantageous to reduce the number of optimization variables (independent of the number of layers) and introduce a convex design space, thus making it possible to obtain a globally optimal solution. However, lamination parameters (LPs) are not independent design variables; therefore, it is difficult to include, e.g., composite failure criteria and design and manufacturing constraints. In addition, it is limited to considering one candidate material and does not generate a direct description of the laminate data for the design. As a result, LPs require additional optimization steps to convert the stiffness properties to optimal fiber orientation angles to introduce design guidelines and manufacturing constraints. Therefore, a multi-level optimization strategy is used to exploit the benefits to achieve global optima at its first stage. However, despite these methods' popularity, it limits the capability of CF4 processes that enable multi-axial and  
Figure 6: MBB—post-processed design result of FRC structure with fixed (**top-row**) and varying fiber volume fraction (**bottom-row**) using a micro-structure unit cell with rectangular-shape (**left-column**) and cross-shaped (**right-column**) fiber layout. The black color represents matrix material, and the yellow colored part is fiber material [130]. micro-scale prints. In addition, it must consider AM-related manufacturing constraints, e.g., minimum turning angles, feature sizes, etc., such that these constraints are concurrently evaluated in the optimization process to achieve realizable AM design. Thus, the framework currently does not offer scalability for numerical verification of the CF4 prints. The LPs framework is briefly discussed for completeness on available parameterization schemes. Still, interested readers can refer to the review by [PERSON] et al. [139] and recent work on the TO of laminates in the following citations [140; 141; 142; 143]. Continuous orientation methods naturally become a suitable parameterizing scheme for CF4 processes because these methods provide the highest freedom regarding shape and variable stiffness.