In this paper, the post-processing of 3D-printed poly lactic acid (PLA) parts is investigated. Workpieces are manufactured by fused deposition modeling (FDM) 3D printing, while they may have defects in some areas such as edges. A post-processing is introduced here for 3D-printed samples by low power CO₂ laser. The thickness of the FDM samples are 3.2 mm and printed by optimum conditions. Effects of process parameters such as focal plane position (−3.2–3.2 mm), laser power (20–40 W), and laser cutting speed (1–13 mm/s) are examined based on the design of experiments (DOE). Geometrical features of the kerf; top and bottom kerf; taper; ratio of top to the bottom kerf are considered as output responses. An analysis of the experimental results by statistical software is conducted to survey the effects of process parameters and to obtain regression equations. By optimizing of the laser cutting process; an appropriate kerf quality is obtained and also optimum input parameters are suggested. Experimental verification tests show a good agreement between empirical results and statistical predictions. The best optimum sample with 1.19 mm/s cutting speed, 36.49 W power and 0.53 mm focal plane position shows excellent physical features after the laser cutting process when 276.9 μm top and 261.5 μm bottom kerf width is cut by laser.

In this paper, the influence of layer thickness (LT), infill percentage (IP), and extruder temperature (ET) on the maximum failure load, thickness, and build time of bronze polylactic acid (Br-PLA) composites 3D printed by the fused deposition modeling (FDM) was investigated via an optimization method. PLA is a thermoplastic aliphatic polyester obtained from renewable sources, such as fermented plant starch, especially made by corn starch. The design of experiment (DOE) approach was used for optimization parameters, and 3D printings were optimized according to the applied statistical analyses to reach the best features. The maximum value of failure load and minimum value of the build time were considered as optimization criteria. Analysis of variance results identified the layer thickness as the main controlled variable for all responses. Optimum solutions were examined by experimental preparation to assess the efficiency of the optimization method. There was a superb compromise among experimental outcomes and predictions of the response surface method, confirming the reliability of predictive models. The optimum setting for fulfilling the first criterion could result in a sample with more than 1021 N maximum failure load. Finally, a comparison of maximum failure from PLA with Br-PLA was studied.

The field of additive manufacturing (AM) has seen a transformation in the production of intricate and complex parts for various applications. Fused Deposition Modelling (FDM), among AM techniques, has garnered significant attention, particularly in fields like fibre-reinforced composites (FRC). In this study, the world of FDM-printed Polylactic Acid (PLA) components is explored, with a focus on how mechanical properties are influenced by infill percentages and layer widths. Through the utilisation of Response Surface Methodology (RSM), the optimisation of FDM-PLA 3D printing for a wide range of biomaterial applications is achieved, along with the unveiling of the potential for remarkable improvements in mechanical performance. Notably, a remarkable 91% reduction in surface roughness for PLA composites was achieved, accompanied by an impressive 25.6% and 34.1% enhancement in the tensile strength and Young’s modulus of fibre-reinforced PLA composites, respectively. This work, positioned at the crossroads of FDM, lays the groundwork for substantial advancements in the realm of additive manufacturing.

Shape memory alloys (SMAs) are types of materials that can restore their original shape upon severe or quasi-plastic deformation, being exposed to specific external stimuli, including heating, electric current, magnetic field, etc. They are a category of functional materials that provides superelasticity as a significant material property. The roots of this unintentional discovery were in the 20th century, and later it attracted the attention of various industries, including aerospace, medical, mechanical, manufacturing industries, etc. Later developments mainly focused on improving the properties of these materials. One of the ways in which this is achieved is the application of intensive plastic strains on SMAs through severe plastic deformation (SPD) methods, leading to extreme grain refinement. Superelasticity is a key characteristic of SMAs and is known as the capacity of a polycrystalline material to display extremely high elongations before failure, in a typically isotropic way, with an approximate strain rate of 0.5. Utilization of SPD techniques can also affect and lead to superior superelasticity responses in SMAs. Several SPD methodologies have been introduced over the decades, to produce ultrafine-grained and even nanostructured materials, including constrained groove pressing, equal-channel angular pressing, high-speed high-pressure torsion, accumulative roll bonding, etc. This paper aims to present a clear view of the mechanical properties and microstructure evolution of shape memory alloys after processing by some SPD methods, and to show that SPD methods can be a great option for developing SMAs and expanding their industrial and technological applications.

This paper explores the 3D printing of poly vinyl alcohol (PVA) using the fused deposition modeling (FDM) process by conducting statistical modeling and optimization. This study focuses on varying the infill percentage (10–50%) and patterns (Cubic, Gyroid, tri-hexagon and triangle, Grid) as input parameters for the response surface methodology (DOE) while measuring modulus, elongation at break, and weight as experimental responses. To determine the optimal parameters, a regression equation analysis was conducted to identify the most significant parameters. The results indicate that both input parameters significantly impact the output responses. The Design Expert software was utilized to create surface and residual plots, and the interaction between the two input parameters shows that increasing the infill percentage (IP) leads to printing heavier samples, while the patterns do not affect the weight of the parts due to close printing structures. On the contrary, the discrepancy between the predicted and actual responses for the optimal samples is below 15%. This level of error is deemed acceptable for the DOE experiments.

Background The severe plastic deformation approach and its well-known cyclic extrusion compression (CEC) method have been established as a powerful tool for fabricating bulk ultrafine-grained metals and alloys with improved properties. Objective This study focused on the microstructure evolution, hardness behavior, and corrosion properties of the CEC-processed Al5052 up to four passes compared to the initial annealed state. Methods The initial and CEC-processed Al5052 samples at different pass numbers were examined experimentally by EBSD analyses, hardness measurements, and corrosion resistance. Results Substantial grain refinement was attained from ~23 μm for the annealed sample to ~0.8 μm in the four passes sample. In addition, the hardness values considerably increased up to 75.7% after four passes from the initial value of 80 HV. In addition, the increment of pass numbers led to a more uniform dispersion of hardness values. Furthermore, the production of more stable protective oxide layers on the UFG structure of the CEC-processed sample led to the improvement in electrochemical response with a corrosion rate reduction from 1.49 to 1.02 mpy, respectively, in the annealed and final pass CEC-processed samples. In fact, the annealed sample manifested more large-sized and deeper pits than the CECed samples due to the increment of potential values and electrochemical attack of chlorine ions that finally deteriorates the corrosion performance. Conclusions CEC is an efficient method to improve the mechanical properties of materials due to substantial microstructural changes along with enhancement of electrochemical behavior because of the presence of small-sized and shallow pits.