# Evaluating the Reliability of Powder Bed Fusion for Biomedical Materials: An Experimental Approach
## 1 Introduction  
Powder Bed Fusion (PBF) is replacing the former terminology of Selective Laser Melting (SLM), according to the new AM standards. PBF is an additive manufacturing (AM) technique capable of fabricating parts directly from three-dimensional models. As a powder bed fusion technology, PBF involves exposing a powder bed to a high-density laser beam, causing the powder to fully melt and solidify upon cooling [1]. This process offers new perspectives in material science, design optimization, and application development [2]. PBF technology provides increased geometrical freedom in designing customized parts with complex shapes, which can be fabricated using various methods for applications in the automotive, aerospace, and biomedical industries [3; 4; 5; 6]. Despite its advantages, the PBF process is not without challenges. Parts manufactured by PBF may exhibit defects such as weld cracking and shrinking after removal from the platform [7]. Ductility-dip cracking is suggested as one of the key mechanisms by which these cracks form during fabrication [8]. Various studies have investigated the character and mechanisms of cracking in PBF technology, focusing on processing parameters for different metals where cracking could be minimized but not eliminated [1; 7; 8; 9; 10; 11]. These studies highlight major defects and case studies where balling effect, microscopic and macroscopic cracks, heat-affected zones, residual stress phenomena, or un-melted areas could appear. The studies presented in [12; 13] highlight the importance of process parameters like laser-scanning velocity, laser power, hatch space, and scanning pattern in determining the temperature and stress fields during the LPBF process. Higher laser power increases the melt pool size and maximum temperature, which can lead to higher thermal residual stress. Conversely, increasing hatch spacing can reduce the thermal gradient and residual stress, improving the overall quality of the manufactured parts. The laser-scanning pattern also influences the thermal gradient and residual stress distribution, affecting the cooling stage and final part properties. New studies highlight the potential of machine learning to revolutionize additive manufacturing by enabling precise control over material properties and process parameters [14; 15]. To address these challenges, common methods to decrease residual stress levels after PBF manufacturing include heat treatment or hot isostatic pressing [16; 17; 18; 19]. [PERSON] and [PERSON] showed that the PBF parts exhibit considerable anisotropy of their microstructures and uneven mechanical characteristics, which may prevent their widespread application. Positive effects may be archived by hot isostatic pressing [14]. However, more significant research is necessary to determine the effect of PBF processing parameters on residual stress [11]. As an emerging technology, there has been limited investigation into the influence of process parameters on PBF processability. [PERSON] et al. found that optimizing the PBF process for commercially available powders is laborious, and even slight changes in the powder can strongly affect the micro-cracking [20]. Most of previous studies were focused on optimizing process parameters with different aims, such as reducing surface roughness, increasing part density, or improving mechanical characteristics. For example, [PERSON] et al. explore the process strategy and point out major factors that should be considered to obtain a better quality of PBF-printed mechanisms [21]. Also, [PERSON] et al. investigate the PBF parameters to improve the density of CoCrMo femoral protheses (99%) and to reach a superior mechanical resistance (1061 MPa) [22]. However, these were individual improvements, and achieving consistently high-quality PBF parts has been challenging [20; 21; 22]. The quality of the powder layer in the PBF process is crucial for achieving high-quality final parts. Key aspects of powder layer quality include uniformity, smooth layering, and high packing density [23; 24; 25].