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Selective laser melting (SLM) is an emerging additive manufacturing (AM) technology for metals. Intricate three-dimensional parts can be generated from the powder bed by selectively melting the desired location of the powders. The process is repeated for each layer until the part is built. The necessary heat is provided by a laser. Temperature magnitude and history during SLM directly determine the molten pool dimensions, thermal stress, residual stress, balling effect, and dimensional accuracy. Laser-matter interaction is a crucial physical phenomenon in the SLM process. In this paper, five different heat source models are introduced to predict the three-dimensional temperature field analytically. These models are known as steady state moving point heat source, transient moving point heat source, semi-elliptical moving heat source, double elliptical moving heat source, and uniform moving heat source. The analytical temperature model for all of the heat source models is solved using three-dimensional differential equations of heat conduction with different approaches. The steady state and transient moving heat source are solved using a separation of variables approach. However, the rest of the models are solved by employing Green’s functions. Due to the high temperature in the presence of the laser, the temperature gradient is usually high which has a substantial impact on thermal material properties. Consequently, the temperature field is predicted by considering the temperature sensitivity thermal material properties. Moreover, due to the repeated heating and cooling, the part usually undergoes several melting and solidification cycles, and this physical phenomenon is considered by modifying the heat capacity using latent heat of melting. Furthermore, the multi-layer aspect of the metal AM process is considered by incorporating the temperature history from the previous layer since the interaction of the layers have an impact on heat transfer mechanisms. The proposed temperature field models based on different heat source approaches are validated using experimental measurement of melt pool geometry from independent experimentations. A detailed explanation of the comparison of models is also provided. Moreover, the effect of process parameters on the balling effect is also discussed.

Grinding has become one of the most efficient precision machining methods to treat with undesired machining defects and improve the surface integrity for the hard and brittle engineering ceramics. However, it is inevitable to cause micro-damages and related transformation of microscopic features, which will eventually affect the grinding quality. This paper is devoted to investigate the high-speed grinding microscopic features of silicon carbide ceramics to reveal the application of high-speed grinding technique in precision machining of ceramics. A comparative study of high-speed and conventional speed grinding of silicon carbide ceramics is discussed in terms of phase transformation, residual stresses, micro-damages, grinding chips, and surface topography. The results show that the high-speed grinding (HSG) process could help substantially improve the workpiece integrity in terms of better surface finish, smaller damages, and controlled residual stresses with a higher material removal rate. Moreover, it has also been proved that a polytypic phase transformation could be induced in HSG process.

The machining residual stress generated on the surface of the machined parts during machining has a crucial influence on the machining accuracy, fatigue strength, and corrosion resistance of the parts. Tool wear will aggravate the tool-work friction, and the thermal and mechanical load will change significantly, affecting the residual stress distribution. The distribution of 3D oblique cutting mechanical stress and thermal stress during tool wear is predicted by analyzing the 3D contact state of quick oblique cutting. The incremental thermal-elastic–plastic method is used for stress loading, and the 3D relaxation method is used for stress release to obtain residual stress. An analytical residual stress model considering tool wear is proposed to predict the residual stress distribution in milling, while aluminum alloy 7075-T6 is used as the workpiece in the case study. The results show that with the increase of tool wear, the residual stress of machined surface transfers from compressive stress to tensile stress, the value of sub-surface residual compressive stress increases the peak value of compressive stress moves more resounding, and the thickness of residual stress layer increases significantly. The average error between the predicted and experimental values is about 23.3%, which proves the model’s validity and provides a new idea for controlling the distribution of machining residual stress.

Milling with minimum quantity lubrication (MQL) is a commonly used machining technique in the industry because of its advantage in lowering the cutting temperature and cutting force. Among its wide usage in machining, modeling for milling operations was particularly hard for its complexity. This paper proposed an analytical model for cutting force prediction in the end-milling process with MQL. The 3D milling operation was transferred into equivalent 2D orthogonal cutting at each rotational angle. Then the proposed model incorporated updated friction coefficients due to the MQL with boundary lubrication effect. Based on Oxley’s orthogonal cutting model, the cutting force was calculated with an updated friction coefficient. Two sets of validations were done with experimental measurements using different cutting materials. The proposed model delivered reasonable accuracy for the force prediction with MQL, providing an adequate method for the industry. Based on the model investigation, the friction coefficient in cutting was also significantly affected by the droplet’s layer thickness, which was presumably linearly correlated with the flow speed of the lubricant.

The machining induced material microstructure evolution path is determined from the temperature and mechanical loading history. Inversely, the machining forces and machined part surface integrity are dependent on the material microstructure attributes. Most of the previous research work with a microstructure consideration in machining stays largely on the experimental observation stage. A comprehensive thermal-mechanical-microstructure coupled machining process modeling framework is still missing. This paper reviews the recent research work on the material microstructure evolution in the context of machining components. The material microstructure property change on the workpiece material in the machining process are analyzed. The effects of material microstructure evolution on workpiece mechanical properties and surface integrity are investigated. It is concluded that a physical based material microstructure affected machining model is needed for the machining process optimization.

Additive Manufacturing (AM) has become a revolutionary technology in manufacturing, attracting considerable attention in industrial applications recently. It allows for intricate fabrication, reduces material waste, offers design flexibility, and has economic implications. Nonetheless, the residual stresses generated during the AM process and their effects on microstructural evolution and material properties continue to pose significant challenges hindering its advancement. This paper investigates the evolution of microstructures, focusing on texture and grain size as influenced by processing parameters. It examines how these factors affect the performance of multi-phase materials, specifically in terms of elastic modulus, Poisson’s ratio, and yield strength, leading to variations in residual stress through analytical simulation. The authors developed a thermal model that considers heat transfer boundaries and the geometry of the molten pool. They simulated grain size by considering the heating and cooling processes, including thermal stress, the Johnson-Mehl-Avrami-Kolmogorov (JMAK) model, and grain refinement. The texture was simulated using the Columnar-to-Equiaxed Transition (CET) model, thermal dynamics, and Bunge calculations. The self-consistency model determines the properties based on the established texture distribution. Finally, both microstructure-affected and non-affected residual stresses were modeled and compared. Two gaps between microstructure-affected residual stress and non-affected analytical models appear at the depths of 0.02 mm and 0.078 mm. The results indicate that controlling process parameters and optimizing microstructures can effectively reduce residual stresses, significantly enhancing the overall performance of AM components. Hence, this work provides a more accurate analytical residual stress model and lays the foundation for better control of residual stress in the AM industry.

This paper proposes analytical modeling methods for the prediction of balling, lack-of-fusion and keyholing thresholds in the laser powder bed fusion (LPBF) additive manufacturing. The molten pool dimensions were first predicted by a closed-form analytical thermal model. The effects of laser power input, boundary heat loss, powder size distribution and powder packing pattern were considered in the calculation process. The predicted molten pool dimensions were then employed in the calculation of analytical thresholds for these defects. Reported experimental data with different materials were compared to predictions to validate the presented analytical models. The predicted thresholds of these defects under various process conditions have good agreement with the experimental results. The computation time for the presented models is less than 5 min on a personal computer. The optimized process window for Ti6Al4V was obtained based on the analytical predictions of these defects. The sensitivity analyses of the value of threshold to the laser power and scanning speed were also conducted. The proposed analytical methods show higher computational efficiency than finite element methods, without including any iteration-based computations. The acceptable predictive accuracy and low computational time will make the proposed analytical strategy be a good tool for the optimization of process conditions for the fabrication of defects-free complex products in laser powder bed fusion.

In this study, a physics-based analytical method was proposed for the prediction of upper surface roughness in laser powder bed fusion (LPBF). The temperature distribution and molten pool shape in the melting process were first predicted by an analytical thermal model. The cap area of the solidified molten pool was assumed to be half-elliptical. Based on this assumption and the principle of mass conservation, the cap height and the specific profile of the cap area were obtained. The transverse overlapping pattern of adjacent molten pools of upper layer was then obtained, with given hatch space. The analytical expression of the top surface profile was obtained after putting this overlapping pattern into a 2D coordinate system. The expression of surface roughness was then derived as an explicit function of the process parameters and material properties, based on the definition of surface roughness (Ra) in the sense of an arithmetic average. The predictions of surface roughness were then compared with experimental measurements of 316L stainless steel for validation and show acceptable agreement. In addition, the proposed model does not rely on numerical iterations, which ensures its low computational cost. Thus, the proposed analytical method can help understand the causes for roughness in LPBF and guide the optimization of process conditions to fabricate products with good quality. The sensitivity of surface roughness to process conditions was also investigated in this study.

In recent years, medium- and low-volume fraction silicon carbide particle-reinforced aluminum matrix composites (SiCp/Al) have increasingly become a key material in the aerospace industry. Force prediction and material removal mechanism analysis of milling SiCp/Al are necessary to improve the surface integrity of products. An orthogonal experiment of SiCp/2009Al with a volume fraction of 20% was carried out, and the effect of the milling parameters on milling force was studied with the input parameters of milling speed, feed rate, and milling depth. Thereby, the empirical force model of milling SiCp/2009Al is established by fitting the experiential data based on the multiple linear regression analysis methods. Moreover, the effects of the milling parameters on the force were analyzed. Finally, the material removal mechanism of milling SiCp/Al is analyzed based on dislocation theory. The analyzed results reveal that the removal mechanism of the SiCp/Al composites includes plastic deformation of the aluminum matrix, cutting of particles, fragmentation, and deboning. Based on dislocation theory and maximum undeformed thickness theory, the effect of cutting parameters on the form of material removal was analyzed, which serves as a guide for selecting appropriate machining parameters to obtain improved machining quality of SiCp/Al composites.

Due to the characteristics of high brittleness and low fracture toughness of monocrystalline silicon, its high precision and high-quality cutting have great challenges. Aiming at the urgent need of wafer cutting with high efficiency, this paper investigates the influence law of different laser processes on the size of the groove and the machining affected zone of laser cutting. The experimental results show that when laser cutting monocrystalline silicon, in addition to generating a groove, there will also be a machining affected zone on both sides of the groove and the size of both will directly affect the cutting quality. After wiping the thermal products generated by cutting on the material surface, the machining affected zone and the recast layer in the cutting seam can basically be eliminated to generate a wider cutting seam and the surface after wiping is basically the same as that before cutting. Increasing the laser cutting times will increase the width of the material’s machining affected zone and the groove width after chip removal. When the cutting times are less than 80, increasing the cutting times will increase the groove width at the same time; but, after the cutting times exceed 80, the groove width abruptly decreases and then slowly increases. In addition, the lower the laser scanning speed, the larger the width of the material’s machining affected zone and the width of the groove after chip removal. The increase in laser frequency will increase the crack width and the crack width after chip removal but decrease the machining affected zone width. The laser pulse width has a certain effect on the cutting quality but it does not show regularity. When the pulse width is 0.3 ns the cutting quality is the best and when the pulse width is 0.15 ns the cutting quality is the worst.