This paper provides an in-depth review of the advancements and challenges associated with Titanium Matrix Composites (TMCs) in Selective Laser Melting (SLM). Material selection, SLM processing parameters, and their influence on the microstructure and properties of TMCs are discussed. The relationship between processing parameters, material characteristics, and the development of defects such as balling, porosity, and cracking is examined. Critical factors influencing the evolution of microstructure and defect formation in TMCs processed by SLM are highlighted. Strengthening mechanisms such as dislocation movements, grain refinement, the Orowan process, and load-bearing capacity are analyzed, and their roles in enhancing hardness, tensile strength, corrosion resistance, and wear resistance are explored. It is indicated by key findings that less than 5 % reinforcement content by volume can significantly enhance mechanical properties, achieving maximum hardness values of approximately 1000 HV and tensile strength close to 1500 MPa. However, this improvement is accompanied by a notable decrease in elongation. The importance of optimizing SLM parameters such as laser power, scan speed, hatch distance, layer thickness, and particle contents to minimize defects and enhance material performance is underscored. Existing research gaps in defect management and material distribution are identified. Future research directions on improving TMCs performance through advanced SLM techniques are suggested.

This research aimed to optimize the camera calibration process by identifying the optimal distance and angle for capturing checkered board images, with a specific focus on understanding the factors that influence the reprojection error (${ϵ}_{RP}$). The objective was to improve calibration efficiency by exploring the impacts of distance and orientation factors and the feasibility of independently manipulating these factors. The study employed Zhang’s camera calibration method, along with the 2^k full-factorial analysis method and the Latin Hypercube Sampling (LHS) method, to identify the optimal calibration parameters. Three calibration methods were devised: calibration with distance factors (D, H, V), orientation factors (R, P, Y), and the combined two influential factors from both sets of factors. The calibration study was carried out with three different stereo cameras. The results indicate that D is the most influential factor, while H and V are nearly equally influential for method A; P and R are the two most influential orientation factors for method B. Compared to Zhang’s method alone, on average, methods A, B, and C reduce ${ϵ}_{RP}$ by 25%, 24%, and 34%, respectively. However, method C requires about 10% more calibration images than methods A and B combined. For applications where lower value of ${ϵ}_{RP}$ is required, method C is recommended. This study provides valuable insights into the factors affecting ${ϵ}_{RP}$ in calibration processes. The proposed methods can be used to improve the calibration accuracy for stereo cameras for the applications in object detection and ranging. The findings expand our understanding of camera calibration, particularly the influence of distance and orientation factors, making significant contributions to camera calibration procedures.