Combination Of Process Parameters Research Articles

Effect of laser incidence angle on the femtosecond laser ablation characteristics of silicon carbide ceramics

Due to their excellent physical and chemical properties, silicon carbide ceramics have become representative high-performance materials in aerospace, energy power, biomedical, and other fields. However, as a typical hard and brittle material, silicon carbide ceramics possess incredibly high hardness and brittleness, which pose challenges to traditional mechanical processing methods. Laser processing, as a non-contact method, offers a wide processing range and high processing efficiency and has broad application prospects in the field of hard and brittle material processing. In this paper, laser ablations of silicon carbide ceramics with various combinations of process parameters were carried out by using a five-axis infrared femtosecond laser processing system. The changes in the ablation morphology with different incidence angles and laser power were discussed. The results demonstrate that the ablation threshold of silicon carbide ceramics initially increases, then decreases, and finally increases with the increase of laser incident angle. This trend may be attributed to the effect of the incidence angle on the laser absorption rate of silicon carbide ceramics. The ablation morphology of silicon carbide ceramics can be divided into three zones based on color and oxygen distribution: the ablation removal zone, ablation edge zone, and ablation affected zone. At the same laser incidence angle, the ablation range and depth gradually increase with the increase in laser power, but the growth rate gradually decreases. Furthermore, at the same laser power, as the incident angle increases, the laser energy density gradually decreases, and the long axis of the actual ablation area gradually lengthens while the short axis gradually shortens. This work could provides technical and theoretical support for laser surface processing at multiple incidence angles, which is conducive to multi-axis processing of complex curved parts.

Mechanisms of defect formation in Ti-6Al-4V product during re-melting of layers in selective laser melting

Knowledge of defect formation mechanisms in the manufacturing process helps improve product quality. In this study, defect formation due to re-melting of each layer in selective laser melting of Ti-6Al-4V demonstrated the physical behavior in the manufacture of metallic parts. The re-melting strategy was based on scanning with low energy density (ED) and increased ED with various combinations of laser processing parameters. The increased EDs and their parameters, namely laser power, scanning speed, and hatch distance, were selected based on the previous research experience by the authors. The concept of selecting a low ED followed by a high ED was to reduce the spattering of the powder material during the process. The low ED caused partial sintering of the powder, while the high ED caused the melting of the material, resulting in different metallurgical properties of the manufactured parts. Densities, pore properties, porosity in the initial layers, surface morphologies, and microstructures in the defective areas of the samples were studied to determine the effects of re-melting. Advantages and disadvantages were found with respect to the range of applications of the products.

Effects of process parameters on mechanical properties and interface of 3D printed bamboo‐inspired CCFR‐PLA/TPU composites

AbstractInspired by the exceptional strength and toughness of fresh bamboo, a low‐cost method for preparing continuous fiber‐reinforced multi‐matrix composites based on 3D printing was proposed in this paper. Through the design of a special extrusion nozzle, the controllable feed of polylactic‐acid (PLA) and thermoplastic polyurethane (TPU) filaments was achieved, allowing for the preparation of continuous carbon fiber reinforced PLA/TPU composites. The effects of various process parameters on the tensile and flexural properties of the CCFR‐PLA/TPU composites were investigated. Additionally, the relationship between process parameters and the formation of the matrix‐fiber interface and PLA‐TPU interface was analyzed. The results show that layer height has the greatest influence on mechanical properties, while the printing speed has the least influence. The mechanical properties of the CCFR‐PLA/TPU composites and the unreinforced blend matrix, prepared using the optimal combination of process parameters, were tested. The results demonstrated that the tensile strength and flexural strength of the CCFR‐PLA/TPU composites increased by 16.95 and 1.80 times, respectively, compared to the unreinforced blend matrix. Further, inspired by the overall structure of bamboo, a stiffness gradient CCFR composite material was designed and prepared. The methodology employed in this study holds significant implications for the advancement of novel multi‐matrix hybrid continuous fiber reinforced composites, particularly in aerospace and related industries.Highlights Multi‐matrix continuous fiber reinforced composites were prepared by 3D printing inspired by fresh bamboo. The effects of process parameters (nozzle temperature, printing speed, extrusion width, layer height) on mechanical properties were investigated. The optimal printing parameter combination was determined by range analysis. Stiffness gradient composites were prepared inspired by the overall structure of bamboo.

Improving the stability of the friction stir channelling technology via a cooled copper backing plate

The development of the friction stir channelling (FSC) technology has a potential to revolutionize the manufacturing industry, providing an innovative way to produce continuous sub-surface channels in monolithic components in a single step. However, the process generates heat that can lead to defects and loss of stationarity, affecting the quality of the channels produced and the process’ efficiency and control. To address these challenges, a ground-breaking study was conducted using a cooled copper backing plate to adjust the process temperatures and investigate the influence of the temperature on FSC stability. The results of the study showed that the cooled copper backing plate has a significantly higher rate of heat conduction, effectively preventing the processed component from overheating and ensuring that the process maintains its stationarity. When using the steel backing plate, only one combination of process parameters (a rotation speed of 450 rev/min and a traverse speed of 71 mm/min) yielded satisfactory results. Moreover, the use of the cooled copper backing plate allowed for a wider range of process parameters to be employed, resulting in sub-surface channels with higher quality and fewer defects. The 710/71 parameters combination resulted in a lower heat input, while the 900/45 parameters set produced channels with a more rectangular geometry. A rotation speed of 900 rev/min and a traverse speed of 45 mm/min have been shown to be the best choice. This innovative approach to FSC technology represents a major step forward in solid-state manufacturing, envisaging new possibilities for producing longer sub-surface channels with superior quality and greater efficiency.Highlights• Conducting the FSC process at low temperature has improved its stability.• The use of a cooled copper backing plate enabled a broader range of FSC process parameters.• Longer and stabler leak-free sub-surface channels have been produced in aluminium alloys.Graphical

Optimization of process parameters for preparing the hydrophobic surface of aluminum alloy by laser-assisted electrochemical composite etching based on response surface method

To explore the influence of electrolyte concentration, single pulse energy, current density and scan times on the hydrophobic properties of laser-assisted electrochemical composite etching 2024 aluminum alloy surface, the experimental platform of laser-assisted electrochemical composite etching is built. Based on the results of the single-factor experiments, the response surface method (RSM) is chosen to optimize the process parameters. The optimum combination of process parameters is obtained, and the accuracy of the regression equation is verified by experiments. Through residual analysis, the established regression model fits well. By analysis of variance (ANOVA), the sequence of influence of the factors on apparent contact angle (from large to small) is single pulse energy, scan times, electrolyte concentration, and current density. With the maximum apparent contact angle as the goal, the combination of process parameters adjusted after optimization is: electrolyte concentration 2.0 mol/L, single pulse energy 20µJ, current density 18 mA, and scan times 15. Under these conditions, the experimental values of apparent contact angle is 157°, which is close to the predicted value (158°) by the models. The relative errors is 0.6%. It indicates that the regression model is accurate and reliable. This study shows that RSM is an effective method to optimize the process parameters and obtain the ideal experimental results.

Preparation and Characterization of Nano-Silver-Loaded Antibacterial Membrane via Coaxial Electrospinning.

The coaxial electrospinning process has been widely used in the biomedical field, and its process parameters affect product quality seriously. In this paper, the influence of key process parameters of coaxial electrostatic spinning (solution concentration, electrospinning voltage, acceptance distance and liquid supply velocity) on the preparation of a membrane with Chitosan, Polyethylene oxide and nano-silver as the core layer and Polycaprolactone as the shell layer was studied. The optimal combination of key process parameters was obtained by using an orthogonal test, scanning electron microscope, transmission electron microscope and macro-characterization diagram. The results showed that the coaxial electrospun membrane had good mechanical properties (tensile strength is about 2.945 Mpa), hydrophilicity (the water contact angle is about 72.28°) and non-cytotoxicity, which was conducive to cell adhesion and proliferation. The coaxial electrospun membrane with nano-silver has an obvious inhibitory effect on Escherichia coli and Staphylococcus aureus. In summary, the coaxial electrospun membrane that we produced is expected to be used in clinical medicine, such as vascular stent membranes and bionic blood vessels.

Multi-objective optimization of process parameters during friction stir welding of similar AA6061 using MOORA

This work is an attempt to select the optimum process parameters for friction stir welding of similar AA6061 aluminum alloy based on multiple criteria decision-making approach. The friction stir welding experiments have been conducted according to the orthogonal L9 array and the chosen input parameters are tool rotational speed, feed, and tilt angle. The responses measured are tensile strength, hardness, and % of elongation of welded joint. The multi-criteria decision-making technique namely multi-objective optimization based on the ratio analysis (MOORA) is used to find the optimum process parameters combination. The optimum conditions are tool rotational speed of 1120 rpm, feed of 30 mm/rev and tilt angle at 1 o.

Microstructure and magnetic properties of binary Mn54-Al46 alloy particulates obtained by severe plastic deformation processing via end-milling and annealing

We utilize the plastic deformation process associated with the machining operation of end-milling for the preparation of ε-phase Mn-Al particulates with micron scale external dimensions and self-similar shapes from binary as-cast feedstock with composition 54 at.% Mn and 46 at.% Al. The structural evolution and development of magnetic properties in response to the single-pass plastic deformation processing by the end-milling and subsequent thermal annealing have been studied. Effects of end-milling process parameter combinations, primarily the rotational speed of the cutting tool, have been identified to permit genesis of morphological self-similar particulates of ε-phase characterized by cold-worked and sub-micron to nanometer scale refined microstructures. The end-milling derived particulates were suitable for preparation of τ-phase based MnAl particulates with enhanced permanent magnet properties via isothermal annealing. Discernibly higher rates for the exothermic ε-phase decomposition reactions in the end-milling derived particulates have been observed for isothermal annealing at temperatures in the range of 673 K ≤ T ≤ 723 K. The enhanced decomposition reaction kinetics have been attributed to reduced effective nucleation barriers for the respective product phases stemming primarily from reduced grain size. Large saturation magnetization and coercivity in combination with reasonable squareness ratios of the magnetization curves resulted in a (BH)max = 4.2 MGOe for the end-milling derived binary Mn54Al46 particulates obtained for the highest rotational tool speed of 4200 RPM used here after annealing for 20 min at 673 K. The ε-phase Mn-Al particulates derived by end-milling have potential as precursors for the fabrication of τ-phase Mn-Al based PM materials.

A study on the solidification shapes of molten metal droplet impacting at low weber number

In uniform molten metal micro droplet deposition manufacturing (UDDM), the control of droplet solidification shape is essential to meet the forming requirements in different application scenarios to achieve a high forming quality. However, although the prediction of droplet solidification shape has been clearly mastered in a high Weber number application scenario such as thermal spray, droplets generally impact on a substrate at a low Weber number level of 2–10 in UDDM, where the droplet will solidify into various shapes under different processing parameter combinations. Here, to uncover the differentiation mechanism and establish a prediction strategy of the geometric shape of a solidified droplet during print process, the impact events under common forming conditions were systematically investigated by numerical and experimental methods. The solidification shapes of the droplets were roughly assorted into three major categories and a subtype. Results indicate that the solidification shapes are very sensitive to the footprint diameter of the droplet, thereafter an empirical formula for which was derived. On this basis, a mapping of droplet solidification shape to droplet footprint diameter was further developed, which was experimentally verified to be accurate and effective. This work shares a panorama of the solidification shapes of molten droplets impacting at low Weber number. It provides a convenient approach to automatically recognize the contour of a solidified droplet only through measuring the droplet footprint diameter, and more than that, lays a way to artificially tailor the droplet morphology in printing.

Investigation on the performance of wire electrical discharge machining (WEDM) using aluminium matrix composites (AMCs) micro-channel

This study focuses on microchannel fabrication of Al-10% SiC composite using Wire-EDM process with the applications of single variable and multi variable, optimization. This work was targeted keeping in considerations the wider scope of microchannel applications in the fields such as medical, aerospace, automobile, etc. In this research work, the experiment was conducted to achieve high precision and quality surface finish in terms of minimum surface roughness (SR), high material removal rate (MRR), low tool wear rate (TWR) and optimum spark gap (SG). The used experiments were design on the basis of Taguchi design of experiment approach. Four input process parameters were considered namely, pulse on time (Ton), sparking voltage (SV), wire tension (WT), and wire feed rate (WFR). For the experimentation task, the workpeice (Aluminum and silicon carbide (10% Wt SiCmicro)) material, in a desired shape was fabricated through stir casting process. The tool electrode applied for the experiment purpose had specification as, 0.25 mm diameter brass alloy wire (copper 63 percent and zinc 37 percent). For single variable optimization ANOVA (analysis of variance) was applied while as, for multi variables optimization, grey relational analysis (GRA) was applied. The results of the study indicated that, on the basis of single variable optimization, the highest contribution of Ton resulted in case of the performance measures, MRR and SR while as, for TWR and SG, the highest contribution of sparking voltage, observed. Furthermore, the findings of the study indicated that, on the basis of multi variables optimization, the optimal combination of input process parameters is, pulse on time 125 μs, sparking voltage 10 volt, wire tension 12 kgf, and wire feed rate 4 m min−1. These results also get support from the previous research works. The findings of this study be useful for microchannel manufacturing and other related industrial applications.

Multi-Objective Optimization of the Process Parameters of a Grinding Robot Using LSTM-MLP-NSGAII

Grinding robots are widely used in the automotive, mechanical processing, aerospace industries, among others, due to their strong adaptability, high safety and intelligence. The grinding process parameters are the main factors that affect the quality and efficiency of grinding robots. However, it is difficult to obtain the optimal combination of the grinding process parameters only by manual experience. This study proposes an artificial intelligence-based method for optimizing the process parameters of a grinding robot using neural networks and a genetic algorithm, with the aim to reduce the workpiece surface roughness and shorten the grinding time. Specifically, this is the first study utilizing a multi-objective optimization approach to optimize the process parameters of a grinding robot. Based on the experimental data of the grinding robot ROKAE XB7, the long short-term memory (LSTM) and multilayer perceptron (MLP) neural networks were trained to fit the quantitative relationships between the process parameters of the grinding robot, such as feed rate, spindle pressure and pneumatic motor pressure, and the result of grinding surface roughness and grinding time. After that, the non-dominated sorting genetic algorithm II (NSGA-II) was used to calculate the Pareto optimal process parameter combinations using the trained LSTM and MPL model as the objective function. Compared with the method based on manual experience, the process parameters optimized with this method achieved a reduction in surface roughness of at least 13.62% and a reduction in the whole grinding process time of 28%. The excellent grinding results obtained for grinding time and surface roughness validated the feasibility and efficiency of the proposed multi-objective method for the optimization of grinding robots’ process parameters in practical manufacturing applications.

Numerical Modeling, Experimental Investigation, and Optimization of a Micro Hot Embossing Process

Abstract This paper describes the development of a finite element simulation model and a self-made low-cost experimental setup for the micro hot embossing process. The simulation model incorporates stress relaxation behavior through the utilization of the generalized Maxwell model. It also considers thermal expansion and contact friction effects, enabling accurate prediction of the deformed pattern of polymethyl methacrylate (PMMA). Simulations and experiments were performed for various pressure and temperature combinations, and the resulting pattern profile depths were found to be in good agreement, between the simulation and experimental results. In addition, the simulation model was used to generate response surfaces through face-centered central composite design (CCD) to identify the ideal combination of process parameters of the micro hot embossing process for creating a patterned SMD (surface mount device) LED chip panel.

Experimental Study on Carbon Fiber-Reinforced Polymer Groove Machining by High-Power Water-Jet-Guided Laser.

Due to the excellent properties of carbon fiber-reinforced polymers (CFRPs), such as high strength and strong corrosion resistance, the traditional water-jet-guided laser (WJGL) technology has problems with fiber pull-out and has a small cutting depth when processing CFRPs. Therefore, in this study, we used high-power water-jet-guided laser (HPWJGL) technology to perform groove processing experiments on CFRPs. The effects of four key process parameters, high laser power, pulse frequency, feed rate, and water-jet pressure, on the cutting depth were investigated by a single-factor experiment. The formation mechanism of groove cross-section morphology and the processing advantages of high-power water-jet-guided lasers were analyzed. On this basis, the mathematical prediction model of cutting depth was established by using the response surface method (RSM), and the optimal combination of process parameters was obtained. The mathematical prediction model was verified by experiments, and the error was only 1.84%, indicating that the model had a high reference value. This study provides a reference for the precision machining of HPWJGL technology.

Development of a Selective Layer Via Ultrasonic Spray Coating for Vanadium Redox Flow Batteries: Analysis of Ink Composition and Component Scale-up

Vanadium Redox Flow Battery (VRFB) is a promising technology for stationary energy storage because of its long cycle life and independent energy to power ratio. However, the competitiveness of the technology is hindered by some technological issues, such as vanadium cross-over. Vanadium cross-over is the undesired transport of vanadium ions trough the ion-exchange membrane, causing capacity loss and electrolyte imbalance. Usually, to mitigate cross-over fluxes between the two half-cells, relatively thick membranes (>50 µm) are employed in the commercial applications, meaning increased ohmic losses, reduced energy efficiency and higher system capital cost: indeed, the membrane can contribute up to 50% the cost of the stack [1]. The state-of-the-art membranes for VRFB are made of NafionTM because of its high conductivity, but its not-ideal selectivity towards vanadium ions prevents the use of thin membranes. Alternative cation exchange membranes like SPEEK or SPI are promising because of their reduced permeability, but the low conductivity limits system power density. Instead, anion exchange membranes are still limited by the poor chemical stability and low conductivity [2].The authors in a recent work [3] successfully demonstrated the possibility of mitigating vanadium cross-over though an innovative additional selective layer directly deposited on the membrane. The selective layer, termed as barrier, is a porous component whose pores size tortuous path, thickness and composition are designed to improve ion/proton selectivity. As reported in Cecchetti et al., the barrier layer, manufactured through Reactive Spray Deposition Technology (RSDT) significantly reduced battery self-discharge without hindering the efficiency of the battery [3].In this work, the possibility of manufacturing the barrier via Ultrasonic Spray Coating (USC) is investigated. USC is a commercial and easily scalable technique that exploits the ultrasonic vibration of the nozzle tip to uniformly atomize and spray an ink on a substrate [4]. In particular, the influence of the process parameters and ink composition on the selectivity of the barrier layer and efficiency of the battery were investigated through both morphological and electrochemical characterization in batteries of 4 cm2 and 25 cm2 active area. The deposited barrier layers were directly deposited on NafionTM 212 to form thin layers of 10 µm thickness (Figure 1). The barriers were composed of commercial silica and Vulcan® XC-72R nanoparticles, that introduce a tortuous path for the vanadium ions through the separators, and NafionTM ionomer, acting as a binder and ensuring proton conductivity.After identifying the combination of process parameters and ink composition that ensures the lowest self-discharge of the battery, the scale-up of the barrier at commercial scale was investigated by directly deposition the barrier on NafionTM 212 to obtain an active area of 100 cm2. The 100 cm2 barrier was tested in a VRFB in cycles of charge-discharge cycles with cut-off voltages of 1.65 V and 1 V showing a capacity decay rate of 0.11 % cycle-1 at 50 mA cm-2: four time lower than the reference value (0.44 % cycle-1) reported by Rodby et al. for VRFB in the same range of current density [5].

Acquiring Process Knowledge in Extrusion-Based Additive Manufacturing via Interpretable Machine Learning.

Additive manufacturing (AM), especially the extrusion-based process, has many process parameters which influence the resulting part properties. Those parameters have complex interdependencies and are therefore difficult if not impossible to model analytically. Machine learning (ML) is a promising approach to find suitable combinations of process parameters for manufacturing a part with desired properties without having to analytically model the process in its entirety. However, ML-based approaches are typically black box models. Therefore, it is difficult to verify their output and to derive process knowledge from such approaches. This study uses interpretable machine learning methods to derive process knowledge from interpreted data sets by analyzing the model's feature importance. Using fused layer modeling (FLM) as an exemplary manufacturing technology, it is shown that the process can be characterized entirely. Therefore, sweet spots for process parameters can be determined objectively. Additionally, interactions between parameters are discovered, and the basis for further investigations is established.

On the Processability and Microstructural Evolution of CuCrZr in Multilayer Laser-Directed Energy Deposition Additive Manufacturing via Statistical and Experimental Methods

Laser-directed energy deposition (LDED) is a promising technology for coating, repairing, and building near-net-shape 3D structures. However, the processing of copper alloys, specifically, has presented a significant challenge due to their low laser absorptivity at the 1060 nm laser wavelength and high thermal conductivity. This study undertook a methodical examination by employing a 2 kW disk laser, operating at a wavelength of 1064 nm, and a coaxial nozzle head to comprehensively examine the processability of the highly conductive CuCrZr alloy for expanding the range of materials that can be successfully processed using LDED. The investigation focuses not only on optimizing the input process parameters that are the laser power, scanning speed, powder feed rate, and overlap ratio, but also on planning the toolpath trajectory, as these factors were found to exert a substantial influence on processability, geometrical accuracy, and the occurrence of defects such as lack of fusion. The optimal toolpath trajectory discovered involved implementing a zigzag strategy combined with a 90° rotation of the scanning direction. Additionally, a start point rotation was considered between each layer to even out the deposition of the layers. Moreover, a contour with a radial path at the corners was introduced to enhance the overall trajectory. Based on the hierarchal experimental study, the appropriate ranges for the key process parameters that leads to 99.99% relative density have been identified. They were found to be from 1100 up to 2000 W for the laser power (P), and from 0.003 up to 0.016 g/mm for the amount of powder that is fed to the melt pool distance (F/V). Regarding the influence of process parameters on the microstructure of the samples with equal deposition height, it was observed that varying combinations of process parameters within the optimal processing window resulted in variations in grain size ranging from 105 to 215 µm.

Multi-Objective Optimization in Ultrasonic Polishing of Silicon Carbide via Taguchi Method and Grey Relational Analysis.

As high-level equipment and advanced technologies continue toward sophistication, ultrasonic technology is extensively used in the polishing process of difficult-to-process materials to achieve efficiently smooth surfaces with nanometer roughness. The polishing of silicon carbide, an indispensable difficult-to-machine optical material, is extremely challenging due to its high hardness and good wear resistance. To overcome the current silicon carbide (SiC) ultrasonic polishing (UP) process deficiencies and strengthen the competitiveness of the UP industry, the multi-objective optimization based on the Taguchi-GRA method for the UP process with SiC ceramic to obtain the optimal process parameter combination is a vital and urgently demanded task. The orthogonal experiment, analysis of variance, grey relational analysis (GRA), and validation were performed to optimize the UP schemes. For a single objective of roughness and removal rate, the influence degree is abrasive size > preloading force > abrasive content > spindle speed > feed rate, and spindle speed > abrasive size > feed rate > preloading force > abrasive content, respectively. Moreover, the optimal process combination integrating these two objectives is an abrasive content of 14 wt%, abrasive size of 2.5 μm, preloading force of 80 N, spindle speed of 8000 rpm, and feed rate of 1 mm/s. The optimized workpiece surface morphology is better, and the roughness and removal rate are increased by 7.14% and 28.34%, respectively, compared to the best orthogonal group. The Taguchi-GRA method provides a more scientific approach for evaluating the comprehensive performance of polishing. The optimized process parameters have essential relevance for the ultrasonic polishing of SiC materials.

Longitudinal-Torsional Ultrasonic Grinding of GCr15: Development of Longitudinal-Torsional Ultrasonic System and Prediction of Surface Topography.

The common material of bearing rings is GCr15 bearing steel which is a typical difficult-to-machine material. As an important working surface of the bearing, the inner surface of the raceway plays a vital role in the performance of the bearing. As an important means to solve the high-performance manufacturing of difficult-to-machine materials, longitudinal-torsional ultrasonic processing is widely used in various types of processing. In the presented work, the basic size of the horn is obtained from the wave equation of the forced vibration, and the modal analysis and amplitude test are carried out to verify the rationality of the LUTG structure. Then, according to the probability density function of cutting thickness and the overlapping effect of adjacent abrasive trajectories, the LUTG surface topography prediction model is established by using the height formula of the surface residual material, and the model reliability is verified by using the orthogonal test. The error between the test results and the prediction model is within 13.2%. Finally, based on the response surface method, the optimal process parameters that can meet the requirements of low roughness (Ra) and high material removal rate (MRR) are screened, and the optimal combination of process parameters is obtained as follows: A = 4.5 μm, n = 6493.3 r/min, ap = 28.4 μm, and vf = 21.1 mm/min.

A Comparative Study of a Machine Learning Approach and Response Surface Methodology for Optimizing the HPT Processing Parameters of AA6061/SiCp Composites

This work investigates the efficacy of high-pressure torsion (HPT), as a severe plastic deformation mechanism for processing plain and silicon-carbide-reinforced AA6061, with the broader objective of using the technique for improving the properties of lightweight materials for a range of objectives. The interactions between input variables, such as the pressure and equivalent strain (εeq) applied during HPT processing, and the presence of SiCp and response variables, like the relative density, grain refinement, homogeneity of the structure, and the mechanical properties of the AA6061 aluminum matrix, were investigated. Hot compaction (HC) of the mixed powders followed by HPT were employed to produce AA6061 discs with and without 15% SiCp. The experimental findings were then analyzed statistically using the response surface methodology (RSM) and a machine learning (ML) approach to predict the output variables and to optimize the input parameters. The optimum combination of HPT process parameters was confirmed by the genetic algorithm (GA) and ML approaches. Furthermore, the constructed ML and RSM models were validated experimentally by HPT processing the same material under new conditions not fed into the models and comparing the experimental results to those predicted by the model. From the ML and RSM models, it was found that processing the AA6061/SiCp composite HPT via four revolutions at 3 GPa produced the highest mechanical properties coupled with significant grain refinement compared to the HC condition. ML analysis revealed that the equivalent strain induced by the number of revolutions was the most effective parameter for grain refinement, whereas the presence of SiCp played the highest role in improving both the hardness values and the compressive strength of the AA6061 matrices.

Optimization of Selective Laser Sintering Three-Dimensional Printing of Thermoplastic Polyurethane Elastomer: A Statistical Approach

This research addresses the challenge of determining the optimal parameters for the selective laser sintering (SLS) process using thermoplastic polyurethane elastomer (TPU) flexa black powder to achieve high-quality SLS parts. This study focuses on two key printing process parameters, namely layer thickness and the laser power ratio, and evaluates their impact on four output responses: density, hardness, modulus of elasticity, and time required to produce the parts. The primary impacts and correlations of the input factors on the output responses are evaluated using response surface methodology (RSM). A particular response optimizer is used to find the optimal settings of input variables. Additionally, the rationality of the model is verified through an analysis of variance (ANOVA). The research identifies the optimal combination of process parameters as follows: a 0.11 mm layer thickness and a 1.00 laser power ratio. The corresponding predicted values of the four responses are 152.63 min, 96.96 Shore-A, 2.09 MPa, and 1.12 g/cm3 for printing time, hardness, modulus of elasticity, and density, respectively. These responses demonstrate a compatibility of 66.70% with the objective function. An experimental validation of the predicted values was conducted and the actual values obtained for printing time, hardness, modulus of elasticity, and density at the predicted input process parameters are 159.837 min, 100 Shore-A, 2.17 MPa, and 1.153 g/cm3, respectively. The errors between the predicted and experimental values for each response (time, hardness, modulus of elasticity, and density) were found to be 4.51%, 3.04%, 3.69%, and 2.69%, respectively. These errors are all below 5%, indicating the adequacy of the model. This study also comprehensively describes the influence of process parameters on the responses, which can be helpful for researchers and industry practitioners in setting process parameters of similar SLS operations.