Selection Of Process Parameters Research Articles

Correlation of Energy Density and Manufacturing Variables of AA6061 through Laser Powder Bed Fusion and Its Effect on the Densification Mechanism

Aluminum alloy processing via additive manufacturing (AM) technologies has increased in usage during the last decade. AM now enables manufacturing complex geometries not previously achieved through traditional manufacturing. Aluminum is usually processed using laser powder bed fusion (LPBF) technologies, which are used to manufacture metallic components of high geometrical complexity and dimensional accuracy and good mechanical, electrical, and chemical properties, which is why this technology is quite popular at industrial levels. To further develop quality control systems and new aluminum alloys using LPBF, there is a need to establish a predictive relationship between the parameters of the material. A study was carried out to investigate the relationship between energy density and process parameters such as laser power, scan speed, hatch spacing, scan pattern, and laser focus and its influence on the densification mechanism in additively manufactured components with aluminum alloys. AA6061 was selected due to its wide usage in different industries, given its low density and high mechanical performance. Relative density was analyzed using the Archimedes principle, and the quality and morphology of the AA6061 powder were analyzed through metallographic analysis. The process parameter selection was performed according to the best results obtained according to the laser power and energy density factors. The best manufactured samples had an energy density between 30 and 40 J/mm3, with relative densities above 99%.

Analysis of the Effect of Skew Rolling Parameters on the Surface Roughness of C60 Steel Products Using ML Methods.

This paper presents results from experimental and numerical studies of the skew rolling process used to shape axisymmetric products made of C60-grade steel. An experimental study was carried out to investigate the effect of process parameters described by the forming angle α, the skew angle θ, the reduction ratio δ, and the jaw chuck velocity Vu on the surface roughness Ra of the forgings. Stepped forgings made of C60-grade steel were rolled. Based on numerical calculations, a machine learning regression model was developed that uses process parameters to predict the surface roughness of produced parts. The random forest model was found to be the most effective based on the determined metrics (MAE, RMSE, R2). A more detailed analysis of this model was performed using the SHAP library. The application of ML methods will enable optimization of skew rolling through appropriate selection of process parameters affecting improvement in product quality.

Process Analysis and Parameter Selection of Cardiomyocyte Electroporation Based on the Finite Element Method.

Pulsed-field ablation (PFA) has attracted attention for the treatment of atrial fibrillation. This study aimed to further explore the relationship between the transmembrane voltage, pore radius and the intensity and duration of pulsed electric fields, which are closely related to the formation of irreversible electroporation. The different mechanisms of microsecond and nanosecond pulses acting on cardiomyocyte cellular and nuclear membranes were studied. A 3-D cardiomyocyte model with a nucleus was constructed to simulate the process of electroporation in cells under an electric field. Cell membrane electroporation was used to simulate the effect of different pulse parameters on the process of electroporation. Under a single pulse with a field strength of 1 kV/cm and width of 100 μs, the transmembrane potential (TMP) of the cell membrane reached 1.33 V, and the pore density and conductivity increased rapidly. The maximum pore radius of the cell membrane was 43.4 nm, and the electroporation area accounted for 4.6% of the total cell membrane area. The number of pores was positively correlated with the electric field intensity when the cell was exposed to electric fields of 0.5 to 6 kV/cm. Under a nanosecond pulse, the TMP of the nuclear and cell membranes exceeded 1 V after exposure to electric fields with strengths of 4 and 5 kV/cm, respectively. This study simulated the electroporation process of cardiomyocyte, and provides a basis for the selection of parameters for the application of PFA for application toward arrhythmias.

Study of parameters for bioethanol production from Baltic Sea macroalgae

This study aimed to investigate the possibility of producing biofuels from Baltic Sea macroalgae. The scientific value of the article consists in the adaptation of known methods of bioethanol production from seaweeds of the Baltic Sea, selection of processing parameters and bioconversion of macroalgae biomass. Capillary sequencing using amplicon cloning identified four species of macroalgae collected on the coast of the Baltic Sea: Ulva clathrata, Ulva prolifera, Cladophohora fracta, and Ulva intenstinalis. Cellulase and xylanase enzymes, as well as microorganisms Saccharomyces cerevisiae, Lachancea thermotolerans, Pachysolen tannophilus were used to treat macroalgae biomass. Before macroalgae fermentation, acid, alkaline, and enzymatic pretreatments were performed. It was found that bioethanol can be extracted from Baltic Sea macroalgae samples using any of the processing methods considered, but alkaline pretreatment yielded the highest content of 32 %. The Baltic Sea macroalgae can be a potential source of bioethanol, which are alternatives to hydrocarbon fuels.

Vat‐photopolymerization‐based complex ceramic: Optimization of slurry, printing process, and postprocessing parameters

AbstractVat photopolymerization is an effective and economical method for preparing ceramic specimens with complex structures. However, the improper selection of process parameters during the preparation process limits the scope of its application. In this study, the most suitable shear rate was determined based on the solid content and rheological properties of the ceramic slurry. In addition, the specific printing‐process parameters were objectively selected, and the gray correlation method was used to determine the improved weight resolution coefficient through orthogonal experiments combined with the entropy weight method to select the most suitable printing parameters. Finally, the main debinding and sintering parameters that affect the heat treatment performance were considered, and multiple characterization methods were used to detect the specimens and study the impact of parameter changes on specimen performance. The experimental results show that when the laser power is 210 mW, the slice layer thickness is .04 mm, the scanning spacing is .05 mm, and the filling mode is XY, the green bodies have the best forming quality. When the sintering temperature is 1600°C, and the holding time is 4 h, the specimens have the best mechanical properties (the flexural strength reaches 114 MPa).

Prediction of time-varying dynamics and chatter stability analysis for surface milling of thin-walled curved CFRP workpiece

Machining curved surfaces for thin-walled components is always challenging. Due to the strong anisotropic features of carbon fiber reinforced plastic (CFRP), new challenges, such as prediction accuracy loss, have emerged for avoiding the chatter of machining thin-walled curved CFRP workpieces. This paper studied the influence of the anisotropic properties of CFRP workpieces and time-varying dynamics on surface milling stability. An improved damping and time-varying dynamics prediction model was proposed integrated with FEA and numerical calculation considering the change of cutting position, the materials removed, and the anisotropic features of CFRP. Then, the 3D stability lobe diagram (SLD) was achieved by considering the dynamic change at each cutter point on the machining path and dynamic cutting forces based on the instantaneous fiber cutting angle. Based on the obtained 3D SLD, CFRP milling chatter could be accurately avoided, and machining efficiency could be improved. A case study of milling a thin-walled toroidal surface was conducted for validation. In the machining process of CFRP, unlike homogeneous materials such as metals, the natural frequency of CFRP fluctuates nonlinearly with the change curve of material removal within a specific range. Under a higher material removal rate, the surface roughness of the machined surface has been reduced by 74%, Ra below 2.35 µm, based on the selected process parameters of the novel-established SLD, compared to the surface roughness, Ra close to 9.21 µm, obtained by the previous method without considering the time-varying dynamics.

A comparative study of multiple-criteria decision-making methods for selecting the best process parameters for friction stir welded Al 6061 alloy

The selection of welding process parameters is a tedious operation that demands the process evaluation. Multi criteria decision-making strategies for assessing friction stir welding (FSW) process parameters are scanty. Therefore, a comparative study between five different multi-criteria decision-making methods was applied within friction stir welding process to show the deviations in the ranking of the alternatives. The goal is to find the welding parameters (including rotation speed, shoulder diameter, and travel speed) that result in the highest performance scores or rankings for the considered responses, such as ultimate tensile strength, hardness, and surface roughness. In the following, different decision-making strategies (including TOPSIS, GRA, hybrid GRA-TOPSIS, CoCoSo, and MACROS) are applied to calculate the weight of all different decision-making using entropy. The proposed methods in this study are validated by representing the accurate decision maker’s preferences and consideration of uncertainty. The decision-makers choose GRA-TOPSIS and TOPSIS as the best approach with higher efficiency. GRA was determined to be more time-consuming and to have the most variety of outcomes, whereas CoCoSo and MACROS were unable to produce a definite best result. The study is highly promising for researchers and machining specialists to produce quality friction stir welds.

Experimental investigation on tool pin profile for defect-free multi-layered laminates using friction stir additive manufacturing

Friction stir additive manufacturing (FSAM) is a sub-set of solid-state additive manufacturing technique that falls under sheet lamination additive manufacturing. This technique employs friction stir welding (FSW) to produce large, multi-layered parts via the plate addition method. Sufficient heat generation and material mixing are the basic requirements of FSAM, which are primarily dependent on the tool pin profile and the optimal selection of process parameters. Therefore, three tools with distinct pin profiles were selected (plain cylindrical, cylindrical threaded, and taper threaded) at variable tool transverse speeds (20, 40, 60 mm/min). The current study investigates the influence of pin profile and welding speed on material mixing and heat generation, specifically in terms of defects produced between the bonded layers of aerospace aluminum alloy Al-7075. A tool rotational speed of 500 rpm and 1200 rpm with a tool tilt angle of 2.5° were employed for all three tools to develop a 4-layered laminate. It was observed that among all, taper threaded tool pins produced defect-free laminates at 500 and 1200 rpm for all three welding speeds. This was attributed to the higher microhardness with grain size ranging from 0.96 μm to 1.47 μm. Overall, a 95.61 % reduction in grain size was achieved using the taper threaded tool pin profile compared to the as-received base material. Microhardness was enhanced with the increase in transverse speed and building height, furtherer highlighted with statistical analysis.

The effect of selective laser melting process parameters and remelting scanning strategy on relative density and surface hardness of stainless steel 316L

Selective laser melting (SLM) process is the foremost metal additive manufacturing (AM) technology that precisely generates complex geometries from CAD files. Mechanical behavior of printed parts is greatly affected by printing parameters and defining the optimal values of the process parameters to enhance the mechanical properties of components is highly regarded. In this work, four different SLM parameters including scanning speed, laser power, hatch spacing and scan pattern angle were applied to manufacture SS316L parts. For investigating the effect of each parameter and their interactions on hardness and relative density, Taguchi L16 orthogonal array was employed. The influence of part geometry and remelting is also evaluated in order to optimize the hardness and relative density of components. The results exhibited that the laser scanning speed was the most predominant SLM parameter for investigated mechanical properties. Analyzing the regression formula obtained from the results showed that the optimum laser energy density resulted in a 0.37% and 5.38% increase compared to the lowest relative density and hardness, respectively. High remelting energy associated with low remelting scanning speed, caused an 8.5% and 17.9% rise in hardness of squares and triangles, respectively; however, it led 12.5% reduction in hardness for circles. Remelting caused a 2.32% reduction, 2.1% increase and 5.3% rise on relative density for circles, squares and triangles, respectively.

Investigations of selected influencing process factors for transient liquid phase soldering (TLPS) as a die-attach method for automotive power modules

Increasing the operating temperatures in power electronic applications cause a decreasing lifetime of the die-attach interconnection. Transient liquid phase soldering (TLPS) is able to create a reliable and high temperature resistant connection layer via diffusion processes in the form of intermetallic phases with melting points up to > 400°C. This study concentrates on a TLPS reflow-soldering process with a tin-copper-tin (Sn-Cu-Sn) layered preform. During the soldering process the influence of the selected process parameters for the Sn-Cu-Sn on the grown intermetallic phase interconnections between the preform and the components are investigated via the average void percentage and a process capability analysis (cpK). The application of mechanical pressure decreases the average void percentage below 10%. Due to the lower average void percentage the influence of the holding time, peak temperature and heating gradient are examined under low pressure. The biggest impact shows the heating gradient. With a slow heating gradient, the thermomechanical stress decreases by increasing the solubility and the average void percentage could be reduced to less than 2.7 %. In combination of the optimized selected process factors it is possible to reach a process capability value of 1.

Optimization of the Morphology of the Removal Function for Rotating Abrasive Water Jet Polishing.

Abrasive water jet polishing has significant advantages in the manufacturing of complex optical components (such as high-slope optical component cavities) that require high-precision manufacturing. This is due to its processing process, in which the polishing tool does not make direct contact with the surface of the workpiece, and instead maintains a considerable distance. However, the removal functions of most existing abrasive water-jet polishing technologies do not possess strict symmetry, which significantly impacts the ability to correct surface figure errors. Therefore, this study implements rotating abrasive water-jet polishing based on traditional abrasive water jet processing to optimize the removal function, which turns it into a Gaussian form; thus, obtaining a type of removal function more suitable for CCOS polishing. This paper derives an empirical formula between the distance s' from the peak removal point of the removal function to the stagnation point and the nozzle tilt angle α, based on geometric relationships and experimental results, analyzes the relationship between material removal efficiency, nozzle tilt angle, and standoff distance. Finally, this paper verifies through experiments the validity of this empirical formula under different process parameters. Therefore, this study obtains the process conditions that allow rotating abrasive water-jet polishing technology to achieve a stable Gaussian form removal function, and the appropriate process parameters to be selected in conjunction with polishing efficiency; thereby, effectively improving the removal function's corrective ability and manufacturing efficiency. It provides theoretical support for the processing capability and process parameter selection of abrasive water-jet polishing technology, solves the problem of limited shaping capability of existing abrasive water jet tools, and significantly improves the manufacturing capability of high-end optical components.

Improvement of tensile strength of fused deposition modelling (FDM) part using artificial neural network and genetic algorithm techniques

PurposeThis paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.Design/methodology/approachI-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.FindingsThis study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.Research limitations/implicationsThe fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.Practical implicationsThis study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.Originality/valueThe proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.

Process Parameter Optimization of Aerospace-Grade Dissimilar Aluminium Alloy 7075 and 2014 by Friction Stir Welding

In friction stir welding process, the selection of optimum process parameter is an important step. To make a welding with high quality in all aspects such as defect free and reduced HAZ region, it becomes necessary to choose the parameter in such a way the temperature developed due to heat generation is in optimum level. A study on the effect of process parameters on temperature distribution and HAZ region is performed for dissimilar combination of AA7075 and AA2014. A statistical model based on Box-Behnken RSM is built to study the interaction effect of parameters on temperature distribution and optimization of process parameter is obtained as is Tool Rotational Speed (TRS) – 1400 rpm, Tool Traverse Speed (TTS) – 1.21mm/s and Tool Size Ratio (TSR) – 4. An experiment of FSW is made with K-type thermocouples for optimized parameter of AA7075+AA2014 and temperature reading is then compared with simulation for validation of model. The prediction accuracy is in the range of maximum 98.69% and minimum 92.45%. It was observed that optimum depth location of thermocouples is beyond the half of thickness because of less error attained as 1.31%.

Multi-scale modelling for optimization of process parameters of laser powder bed fusion processed Inconel 718 surrogate part

This work uses an analytical and multi-scale thermo-mechanical numerical model to optimise the process parameter to prevent porosity while reducing the distortion in the surrogate part. Taguchi’s experimental design technique was used to identify the effect of process parameters on melt pool evolution. A dimensionless relative melt pool depth ratio (d*) ensures the extent of densification in the simulated part for various processing parameters. The Taguchi analysis outcome revealed an increase in d*, solid ratio, residual stress and distortion with increased laser power while a contrary effect with increased hatch spacing and scan speed. A strong interaction is observed for melt pool metrics and residual stress evolution. However, the interactions for residual stress and distortion evolution are more prominent, showing the influence of process parameters on energy density and thermal gradient evolution. The ANOVA analysis also shows a strong influence of process parameters on melt pool development and residual stress evolution. However, for solid ratio development, scan speed shows an insignificant effect. These observations from meso-scale analysis aids in process parameter selection for defect free part fabrication. A reduction in the VED reduced the magnitude of accumulated residual stresses in the surrogate component, thereby reducing the maximum distortion in the part. A decrease of 8.33 % in maximum distortion is observed for a ∼ 20 % reduction in the VED.

Self-Supervised Learning of Spatially Varying Process Parameter Models for Robotic Finishing Tasks

Abstract This article presents a self-supervised learning approach for a robot to learn spatially varying process parameter models for contact-based finishing tasks. In many finishing tasks, a part has spatially varying stiffness. Some regions of the part enable the robot to efficiently execute the task. On the other hand, some other regions on the part may require the robot to move cautiously in order to prevent damage and ensure safety. Compared to the constant process parameter models, spatially varying process parameter models are more complex and challenging to learn. Our self-supervised learning approach consists of utilizing an initial parameter space exploration method, surrogate modeling, selection of region sequencing policy, and development of process parameter selection policy. We showed that by carefully selecting and optimizing learning components, this approach enables a robot to efficiently learn spatially varying process parameter models for a given contact-based finishing task. We demonstrated the effectiveness of our approach through computational simulations and physical experiments with a robotic sanding case study. Our work shows that the learning approach that has been optimized based on task characteristics significantly outperforms an unoptimized learning approach based on the overall task completion time.

Numerical simulation and surface morphology of laser cladding of nickel-based C276 alloy coatings on AerMet100 steel surface

In order to rationally characterize the laser cladding process and effectively predict the processing results, the temperature field and convective heat transfer at the solid-liquid interface were simulated using ANSYS software. Under the selected process parameters, C276 nickel alloy powder was clad on the surface of AerMet100 steel by laser cladding technology, and the microstructure of the cladding layer was observed to investigate the effects of laser power and scanning speed on the laser results. The effect of laser power and scanning speed on the laser results was investigated. The results show that the best coating performance is obtained when the laser power is 1400 W and the scanning speed is 14 mm/s. When the laser power is 1400 W, the scanning speed is increased from 12 mm/s to 16 mm/s, the dilution rate of the coating is increased from 0.385 to 0.423, and the height of the coating is decreased from 0.706 mm to 0.428 mm. When the scanning speed is 14 mm/s, the laser power is increased from 1000 W to 1600 W, the dilution rate of the coating is increased from 0.375 to 0.511, and the height of the coating is increased from 0.393 mm to 0.662 mm. The laser power has a large effect on the height, width, depth and dilution of the coating, while the scanning speed has a large effect on the average particle size of the coating.

Optimal parameter adjustment of catalytic combustion heaters for oil shale in-situ conversion of low calorific value gases

Oil shale resources are huge, and in order to develop and utilize them rationally, it is crucial to research heaters suitable for downhole in-situ conversion mining. Compared with the problems of short life and multi-stage energy utilization of downhole electric heaters, combustion heaters have advantages such as high thermal efficiency and low cost. The heater uses low calorific value industrial waste gas as the fuel for gas injection, which reduces carbon emissions and environmental pollution and saves gas injection costs. In this paper, we propose to apply catalytic combustion of low calorific value industrial waste gas to generate high temperature exhaust gas suitable for mining, and establish the relationship between gas injection flow rate, combustion chamber parameters and gas injection duration by mathematical methods. The effect of the downhole high-pressure environment on the catalytic combustion characteristics of low calorific gas was simulated and the formula for calculating the content of low calorific gas in the exhaust gas was modified. The results show that the determination of the relational equation solves the problem of excessive axial volume in the design process of downhole heaters. Under high pressure conditions downhole, the exhaust gas temperature and low calorific gas conversion rate are significantly improved. The catalyst ignition temperature ranged from 973 K to 1073 K. Increasing the downhole pressure to 5 MPa increased the conversion of low calorific value gas from 74.56% to 88.22%. The gas injection rate and calorific value range can be calculated by correcting the equation for the content of low calorific gas in the exhaust gas. The conclusion of the study provides a reference basis for the selection of catalytic combustion process parameters for low calorific industrial waste gas, and also provides an important theoretical basis for the construction of the downhole test prototype.

A pilot scale test study with theoretical justification of reaction mechanism for the recovery of chromium(VI) based on solvent extraction using novel centrifugal extractors

As a strategic resource and hazardous substance, the purification and recovery of chromium(VI) from the aqueous phase have attracted attention. In this study, the centrifugal extractor was used to treat the leach liquor of sodium roasting chromite on a pilot scale. The extraction performance and equilibrium distribution of chromium in countercurrent extraction were investigated. Meanwhile, the scrubbing effect of impurities was carefully studied, and the stripping and regeneration effects of the organic phase were tested. Under the selected process parameters, the pilot scale test results, including extraction efficiency of chromium, scrubbing efficiency of impurities, and regeneration performance of the organic phase, were excellent. The qualified (NH4)2Cr2O7 and Cr2O3 products were prepared using the strip liquor, and several physical properties of the products were tested. In addition, the molecular electrostatic potential surface maps, HOMO-LUMO orbitals, Fukui functions, and single point energy of the molecules involved were calculated by Quantum Chemistry. The molecular electrostatic potential analysis, frontiers molecular orbital analysis, Fukui function analysis and interaction energy analysis were applied to investigate the mechanism of separation of chromic acid from impurities in the extraction system.

Multiple criteria decision support analysis for manufacturing process parameters selection of metallic bipolar plates for polymer electrolyte membrane fuel cells

The multi-criteria decision-making method, along with experimental and finite-element (FE) methods, was employed to determine the optimal process parameter values for rubber pad forming of metallic bipolar plates. To achieve this aim, the rubber pad forming process was modeled by FE software, and the results were validated by conducting experimental tests. Three significant rubber pad forming parameters—punch force, hardness, and the thickness of the rubber layer—were considered as input variables. A full-factorial design involving 27 experiments was used to assess the alternatives. Filling percentage, thinning ratio, and stress were considered as distinct evaluation criteria. To solve the multi-criteria decision-making problem, a hybrid approach was used to weigh the alternatives. According to the results, the applied method was capable of selecting the optimal values of process parameters while considering different criteria simultaneously. The results demonstrated that a punch force of 50 kN, rubber hardness of 55 Shore A, and rubber thickness of 3.5 mm were the best processing conditions. For these parameters, the filling percentage, thinning ratio, and stress were 97.6%, 28.5%, and 1005 MPa, respectively.

Numerical Simulation of Temperature Characteristics and Graphitization Mechanism of Diamond in Laser Powder Bed Fusion.

Thermal damage to diamonds is a major limitation in laser powder bed fusion (LPBF) processing of metal matrix diamond composites. In this paper, a numerical simulation model was established to describe the thermal effect of the Diamond-CuSn10 composite on the LPBF process. The simulation results show that the temperature of the diamond presents a double-peak structure, and the double-peak temperature curve shape can be modulated by modifying the laser scanning offset and the size of the diamond powder. And it suggests that the heat of the diamond mainly comes from the transfer of the molten pool. Then, combined with the experimental phenomenon, the mechanism of diamond graphitization in the LPBF process is analyzed. It indicates that since the surface defects of the diamond inhibit the heat conduction of the diamond, the temperature accumulates on the surface, leading to the graphitization of the diamond. Finally, based on this model, the potential of Ti-coated diamonds to prevent and reduce thermal damage in the LPBF process has been extensively studied. It is found that a Ti coating with low thermal conductivity can effectively reduce diamond temperature and improve diamond graphitization resistance. This study can provide a good method and basis for the preliminary selection of LPBF process parameters and the understanding of the graphitization mechanism of diamond tools.