In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

The Ti-6Al-4V lattice structure is widely used in the aerospace industry owing to its high specific strength, specific stiffness, and energy absorption. The quality, performance, and surface roughness of the additively manufactured parts are significantly dependent on various process parameters. Therefore, it is important to study process parameter optimization for relative density and surface roughness control. Here, the part density and surface roughness are examined according to the hatching space, laser power, and scan rotation during laser-powder bed fusion (LPBF), and the optimal process parameters for LPBF are investigated. It has high density and low surface roughness in the specific process parameter ranges of hatching space (0.06–0.12 mm), laser power (225–325 W), and scan rotation (15°). In addition, to investigate the compressive behavior of the lattice structure, a finite element analysis is performed based on the homogenization method. Finite element analysis using the homogenization method indicates that the number of elements decreases from 437,710 to 27 and the analysis time decreases from 3,360 to 9 s. In addition, to verify the reliability of this method, stress–strain data from the compression test and analysis are compared.

Although the Ti–6Al–4V alloy has been used in the aircraft industry owing to its excellent mechanical properties and low density, the low formability of the alloy hinders broadening its applications. Recently, laser-powder bed fusion (L-PBF) has become a novel process for overcoming the limitations of the alloy (i.e., low formability), owing to the high degree of design freedom for the geometry of products having outstanding performance used in hightech applications. In this study, to investigate the effect of bulk shape on the microstructure and mechanical properties of L-PBFed Ti-6Al-4V alloys, two types of samples are fabricated using L-PBF: thick and thin samples. The thick sample exhibits lower strength and higher ductility than the thin sample owing to the larger grain size and lower residual dislocation density of the thick sample because of the heat input during the L-PBF process.

Powder flowability is critical in additive manufacturing processes, especially for laser powder bed fusion. Many powder features, such as powder size distribution, particle shape, surface roughness, and chemical composition, simultaneously affect the flow properties of a powder; however, the individual effect of each factor on powder flowability has not been comprehensively evaluated. In this study, the impact of particle shape (sphericity) on the rheological properties of Ti-6Al-4V powder is quantified using an FT4 powder rheometer. Dynamic image analysis is conducted on plasma-atomized (PA) and gas-atomized (GA) powders to evaluate their particle sphericity. PA and GA powders exhibit negligible differences in compressibility and permeability tests, but GA powder shows more cohesive behavior, especially in a dynamic state, because lower particle sphericity facilitates interaction between particles during the powder flow. These results provide guidelines for the manufacturing of advanced metal powders with excellent powder flowability for laser powder bed fusion.

Ti-6Al-4V alloy has a wide range of applications, ranging from turbine blades that require smooth surfaces for aerodynamic purposes to biomedical implants, where a certain surface roughness promotes biomedical compatibility. Therefore, it would be advantageous if the high volumetric density is maintained while controlling the surface roughness during the LPBF of Ti-6Al-4V. In this study, the volumetric energy density is varied by independently changing the laser power and scan speed to document the changes in the relative sample density and surface roughness. The results where the energy density is similar but the process parameters are different are compared. For comparable energy density but higher laser power and scan speed, the relative density remained similar at approximately 99%. However, the surface roughness varies, and the maximum increase rate is approximately 172%. To investigate the cause of the increased surface roughness, a nonlinear finite element heat transfer analysis is performed to compare the maximum temperature, cooling rate, and lifetime of the melt pool with different process parameters.

The objectives of this study are to examine combustion characteristics of E.V.A. and rubber wastes by fixed-bed incinerator. The results are as follows. Combustion temperature with time rises rapidly, and mass of E.V.A. reduces at short time in E.V.A. combustion. In variation of air-fuel ratio (m), the ideal values of m of E.V.A. and rubber are 2.5, 1.5 respectively. Mixed-waste combustion is more economic than single E.V.A. combustion, because we can get high combustion efficiency (94.0∼99.0%) at 2.0 air-fuel ratio of mixed-waste combustion. Removal efficiencies of SO2 at cooling tower are about 20%. The combustion efficiencies of rubber are over 98.0% according to the experimental conditions.