Influence Of Process Parameters Research Articles

The Influence of Polymer Impregnating Materials on Structural Strengthening of 3D Printed Sand Molds Produced by Binder Jetting Method.

Additive manufacturing offers great potential for various industrial solutions; in particular, the binder jetting method enables the production of components from various materials, including sand molds for casting. This work presents the results of an extensive set of experiments aimed at enhancing the structural strengthening of 3D-printed sand molds. Structural strengthening was achieved by impregnating the sand-printed structures with two polymer materials: epoxy resin and silicone varnish. Impregnation was performed with variable parameters, such as temperature, pressure, and time. Structural strengthening using polymers was investigated by analyzing the flexural strength and impact resistance of the impregnated products and comparing these obtained values with the reference material in terms of impregnation parameters and the polymer used. Microstructural observations and an analysis of the pore filling were also performed. This approach allowed for a full assessment of the influence of processing parameters and the type of polymer used for impregnation on the properties of sand-printed structures, which allowed for identifying the most optimal method to be used to strengthen the sand molds for casting the components for electrical devices. As a direct proof of concept, it was shown that impregnation with polymeric materials could effectively strengthen the sand mold, increasing its flexural strength and impact resistance by over 20 times and 5 times, respectively. A full-scale mold was printed using binder jetting, impregnated with epoxy resin at 65 °C, and used to successfully fabricate a fully functional electrification device.

Optimization of Laser Cladding Process Parameters and Analysis of Organizational Properties of Mixer Liners.

Aiming to address the wear and replacement inconvenience of concrete mixer liners, this study utilizes a laser cladding system to clad Fe60 alloy powder on the liner. It investigates the influence of different process parameters on the forming quality of the Fe60 alloy powder cladding layer. The optimal process parameters were obtained by weighted comprehensive evaluation, and single-layer multi-pass cladding experiments were carried out under the optimal process parameters to investigate the effects of a 30%, 40%, and 50% lap rate on the surface flatness and forming quality of the cladding layer. Using a metallographic microscope, a scanning electron microscope analysis of the macro morphology and microstructure of the cladding layer was conducted, a DPT-5 penetration flaw detector was used to observe the cracks on the surface of the multi-channel cladding, a microhardness tester and friction and wear experimental machine were used for the hardness of the cladding layer, and an abrasive wear resistance test was conducted. The results show that under the process parameters of a laser power of 900 W, powder feeding speed of 7 g/min, scanning speed of 600 mm/min, and 50% lap rate, the average microhardness of the fused cladding layer reaches 742 HV, which is 1.8 times higher than that of the liner plate, and the coefficient of friction is 0.57, which improves the liner plate's wear resistance performance and service life.

Optimal process parameter determination in selective laser melting via machine learning-guided sequential quadratic programing

Selective Laser Melting (SLM) is a widely used additive manufacturing method with critical processing parameters such as Laser Power, Scanning Speed, Hatch Distance, and Laser Beam Diameter, which significantly impact process quality and mechanical properties of fabricated parts like Relative Density, Hardness, and Surface Roughness. This study investigates an effective approach to modeling the SLM process for predicting and optimizing processing parameters using a combination of Machine Learning (ML) and Sequential Quadratic Programing (SQP). The proposed method aims to predict the mechanical properties of SLM-produced AlSi10Mg parts using Machine Learning techniques and then transform the process into a constrained multiple-objective optimization model employing the SQP algorithm to determine optimal process parameters. Artificial Neural Networks (ANN), Gaussian Process Regression (GPR), and Support Vector Machine (SVM) algorithms are applied to establish correlations between process parameters and mechanical properties, represented as mathematical functions. A cost function is formulated using these functions and minimized using the SQP method. Statistical analysis is implemented to validate the influence of processing parameters on mechanical properties accordingly. The outcomes of the method are verified through additional experiments and analyses using Micro-CT scanning techniques. The results demonstrate that processing parameters have a significant impact on part properties across different scales, with Micro-CT scanning proving instrumental in validating mechanical properties. Overall, this study establishes that multiple objectives can be efficiently optimized through the integration of ML and SQP methods, complemented by a judicious number of experiments.

Optimization of laser powder bed fusion process parameter for the fabrication of AlSi12 using NSGA‐II and Pareto search algorithm

AbstractAdditive manufacturing, notably laser powder bed fusion (LPBF), excels in producing complex geometries and is widely used in the automotive, aerospace, and naval industries. Laser powder bed fusion enables the creation of components with the required stiffness and strength at a lighter weight than traditional manufacturing methods. Aluminium alloys are particularly promising for laser powder bed fusion in the automotive and aerospace sectors. To enhance the effectiveness of laser powder bed fusion‐produced components, optimized process parameters must be designed for specific materials. This study investigates the influence of processing parameters, scan speed, scan strategy, and hatch space, on the relative density, surface roughness, and microhardness of AlSi12 samples fabricated by laser powder bed fusion. A Taguchi L27 orthogonal array was used to systematically analyze the effects of these parameters. A regression model was developed and evaluated through analysis of variance using signal‐to‐noise (S/N) ratios to identify optimal parameter values. Results indicated that the scan pattern significantly affects relative density, while hatch space impacts surface roughness and microhardness. Optimal solutions were obtained through multi‐objective optimization using the non‐dominated sorting genetic algorithm (NSGA‐II) and Pareto search algorithms. Experimental validation showed average errors of 0.483 % and 0.461 % for NSGA‐II and Pareto search algorithms, respectively.

A Study of the Influence of Process Parameters of AP PECVD on the Mechanical Properties of Silica-like Films Deposited on Polycarbonate

A Study of the Influence of Process Parameters of AP PECVD on the Mechanical Properties of Silica-like Films Deposited on Polycarbonate

Study on the coupling enrichment process mechanism of volatile oil of Alpiniae officinarum rhizoma from oil-bearing water

The aim of this study is to study the demulsification of oil-bearing water in Alpiniae officinarum rhizoma by the combination of chemical demulsification and membrane separation. Oil-bearing water of A. officinarum rhizoma was demulsification by two methods of inorganic salt-membrane separation and span-membrane separation, and the influence of process parameters was systematically studied by single factor analysis. Then the chemical demulsification process was optimized by orthogonal design (three factors and three levels). The membrane flux and enrichment rate before and after demulsification were measured. The results showed that the membrane flux and enrichment rate of the inorganic salt-membrane separation and demulsification were 2.03 times and 1.18 times higher than those of the undemulsification, and the span-membrane separation was 1.34 times and 1.18 times of that of undemulsification, respectively. The turbidity, viscosity, pH, and particle size of oil-bearing water before and after demulsification were measured, and the correlation between demulsification process, physicochemical properties, membrane flux, and enrichment rate was analyzed. The results indicate that inorganic salt and span change the membrane flux and enrichment rate by decreasing turbidity and increasing particle size. The chemical composition and relative content of volatile oil were similar before and after demulsitioning by GC-MS. The highest relative content was 1,8-eucalyptine (20.05∼51.42%), followed by α-terpineol (11.13∼12.66%), camphene (2.74∼6.75%), camphor (2.29∼4.74%), etc. The results showed that the composition of volatile oil of A. officinarum rhizoma collected by the two demulsification methods remains unchanged, and the inorganic salt-membrane separation was more suitable for the demulsification application of oil-bearing water of A. officinarum rhizoma.

Influence of Process Parameters and its Optimization on Wear Behavior of an Exceptional Aegle Marmelos Polymer/Aluminum Composite

Influence of Process Parameters and its Optimization on Wear Behavior of an Exceptional Aegle Marmelos Polymer/Aluminum Composite

Influence of RSW Process Parameters on Microstructure and Mechanical Properties of Interstitial Free Steel Joints

Influence of RSW Process Parameters on Microstructure and Mechanical Properties of Interstitial Free Steel Joints

Influence of brown algae filler and process parameters on the surface roughness and MRR of jute fiber polymeric composite machined by abrasive water jet

Traditional manufacturing of polymeric composite leads to delamination. Implementing abrasive water jet machining (AWJM) presents a sustainable solution for shaping the polymeric composites, thereby eliminating the need to dispose of chemically contaminated waste. Brown microalgae, commonly found in aquatic environments, serve as viable additives for enhancing the properties of polymeric composites. This study entails the polymeric composite reinforced with jute fiber fabricated by modulating the weight percentages of brown algae powder by 0, 3, and 6 wt.% utilizing the hand layup procedure. The composites were formed and subsequently subjected to drilling by AWJ machining filled with brown algae. The experimental investigation was done to analyze the effect of AWJ parameters: water jet pressure (WJP), traverse speed (TS), and stand-off distance (SoD)—on the material removal rate (MRR) and average surface roughness ( Ra). Orthogonal Array L27 experimental results revealed that polymeric composite reinforced with jute fiber containing 3 wt.% of brown algae exhibited the highest MRR, with an increase of up to 12% compared to other samples. Additionally, these composites demonstrated a significant reduction in surface roughness, reaching up to 8% when compared to alternative samples. Utilizing the Taguchi-based ANOVA method facilitated a systematic exploration and identification of influential factors impacting both MRR and Ra in AWJ machining. Notably, the WJP and SoD emerged as key factors significantly influencing both MRR and Ra.

An integrated approach to sustainable mine wastewater treatment: Magnesium recovery with anion exchange membranes

With recent emphasis on sustainable and efficient mineral valorization, novel approaches to treating mineral wastewater in natural settings bring both environmental and economic value. This paper presents the results of an applied research to develop an integrated approach to sustainable wastewater treatment that includes an ion exchange process to recover copper and cobalt from mine wastewater, followed by the membrane recovery of magnesium. The paper investigates magnesium hydroxide crystallization process employing an anion exchange membrane (AEM) cell. This process involves the penetration of OH- ions from the alkaline solution through the AEM to the feed solution in exchange for Cl- ions and precipitation of Mg(OH)2 as solid particles. The wastewater was sampled from different mine waste sources from the copper mine tailings dam in South Australia, all containing significant amounts of critical metals, including magnesium, copper, and cobalt. The results have demonstrated the potential for sustainable magnesium hydroxide recovery methods. The findings suggest that the most influential process parameters for magnesium hydroxide recovery and purity are magnesium concentration in the feed solution and sodium hydroxide to magnesium ratio in the alkaline solution and feed solution, respectively. It was also established that the overall recovery of cobalt, copper and magnesium in a combination of ion exchange and AEM processes was achieved at a level near 100 %. The purity of magnesium hydroxide precipitate was achieved in the range of 90–96.6 % and depends mainly on the presence of impurities in brine.

Influence of process parameters on the interlaminar shear strength of CF/PEEK composites in-situ consolidated by laser-assisted automated fiber placement

The influence of process parameters, including placement speed, laser power, tooling temperature, compaction force and tape tension, on the interlaminar shear strength of CF/PEEK components in-situ consolidated by laser-assisted automated fiber placement was systematically investigated. To examine both the individual and interactive effects of these parameters, two sets of orthogonal experiments were formulated and conducted, yielding a maximum ILSS of 70.3 MPa. Analysis of variance revealed that the interaction between laser power and placement speed had the most significant effect, followed by tooling temperature, compaction force and tape tension. Furthermore, the concept of linear energy density of consolidated segments (LEDCS) was introduced to characterize and quantify the relationship between laser power and placement speed. ILSS values exceeding 50 MPa were predicted within the LEDCS range of 1.58 J/mm to 3.75 J/mm. Finally, the failure modes of the samples were elucidated through scanning electron microscopy.

Research on laser brazing diamond coating process based on temperature field finite element simulation and machine learning

The temperature of laser brazing diamond seriously affects the quality and service life of diamond tools. In this study, a finite element model of laser brazing diamond was established to achieve digital control of the temperature field during the brazing process. It was determined that the main energy of diamond warming comes from the heat conduction of the molten pool. The maximum temperature value within the brazing layer was proposed as an important indicator of the quality of diamond coating formation. The correlation and local sensitivity of each process parameter to the maximum value of temperature were calculated by a neural network-based machine learning method, and the influence of process parameters on the temperature field was explored. The result of the theoretical analys was finally verified by the coating wear-resistance experiments, and the wear-resistance of the diamond coatings was significantly better than that of other cases when the maximum temperature value in the brazing process was in the range of 1100 °C–1130 °C.

Characterization of bio-crude produced by graphene carbon tetranitrate catalyzed hydrothermal liquefaction and ultrasonication of Ulva prolifera mixed Chicken waste

<p style="text-align:justify;"><span style="font-family:"Times New Roman",serif;font-size:12pt;line-height:200%;">The utilization of macroalgae, specifically </span><em><span style="font-family:"Times New Roman",serif;font-size:12pt;line-height:200%;">Ulva prolifera</span></em><span style="font-family:"Times New Roman",serif;font-size:12pt;line-height:200%;">, for the manufacture of bio-crude demonstrates great potential as a viable alternative to conventional fossil fuels. This is mostly owing to its abundant availability and renewable characteristics, making it an optimal choice for bio-oil production. This study examined the synthesis of bio-crude through the Hydrothermal Liquefaction (HTL) method. The combination of Ultra-sonicated </span><em><span style="font-family:"Times New Roman",serif;font-size:12pt;line-height:200%;">Ulva prolifera</span></em><span style="font-family:"Times New Roman",serif;font-size:12pt;line-height:200%;">, Chicken Waste, and water facilitated the transformation of the moist biomass into Bio-crude. The study also examined the influence of process parameters, including the optimal operational temperature, retention time, and feedstock mixing ratio (275 <sup>o</sup>C, 30 minutes, and 1:4 ratio) for the graphene-C<sub>3</sub>N<sub>4 </sub>catalyst, KOH. The study's findings verified that a significant amount of bio-oil, specifically 23.5wt.% based on dry weight measurements, was successfully produced. The bio-oil mostly consists of alcohols, esters, phenols, ketones, and acidic chemicals. Furthermore, the bio-oil exhibited a significant heating value of 38.15 MJ/kg, which can be attributed to the presence of carboxylic acid groups and aliphatic hydrocarbons. Furthermore, the carbon content in the bio-oil was found to be double that of the macroalgae used as feedstock. Additionally, the heating value of the bio-oil was shown to be 2.5 times greater than that of the macroalgae. Hydrothermal liquefaction may be used to efficiently create bio-oil from </span><em><span style="font-family:"Times New Roman",serif;font-size:12pt;line-height:200%;">Ulva prolifera</span></em><span style="font-family:"Times New Roman",serif;font-size:12pt;line-height:200%;">, a third-generation fuel that has great potential as an environmentally benign and sustainable energy source.</span></p>

Investigating the Impact of Pad Groove Depth Reduction on Process Variation in Oxide Chemical Mechanical Polishing

Abstract The groove depth of a polishing pad diminishes due to continuous wear from the diamond conditioner. Over the course of approximately 20 hours of use, this reduction in groove depth enhances slurry flow across both the pad grooves and surface. A fluid simulation analysis indicates that the new slurry mass fraction at 0.51 seconds increases from 72.34% for an 850 µm groove depth to 100.00% for a 250 µm depth. Consequently, polishing performance metrics including removal rate, within-wafer nonuniformity (WIWNU), and added defects exhibit variations commensurate with groove depth alterations. To explore the influence of process parameters on these polishing performance metrics, oxide film polishing experiments were conducted using pads with initial groove depths of 250, 500, 750, and 850 µm. The effects of process parameters, including pad cut rate, retainer ring pressure, and slurry flow rate on polishing were separately examined across different groove depth pads. Generally, shallow groove pads display improved removal rates but worse WIWNU. Additionally, the maximum surface temperature of the pads was recorded, serving as an indirect indicator of individual parameter effects. The findings have implications for advanced process control, guiding the optimization of polishing protocol in consideration of pad lifetime.

Unveiling the mechanical and microstructural properties of SiC reinforced aluminum wires recycled from scraps by friction stir extrusion

Friction Stir Extrusion (FSE) has been proven as an effective solid-state process to directly recycle metal chips into high-quality wires/rods/tubes. However, the demand for Al-based composite wires with enhanced properties is substantial, and achieving a uniform distribution of the strengthening phase within the composite wire by establishing a robust metal/ceramic interface remains a significant challenge. In this study, AA6082 Aluminum alloy wires reinforced with 12.5 vol% SiC particles, exhibiting homogeneous particle distribution and superior mechanical properties, were successfully produced through the FSE technique. The investigation focused on examining the influence of processing parameters and the addition of SiC reinforcement on the microstructure and mechanical characteristics of the extruded wires. Scanning electron microscopy (SEM), Electron Backscatter Diffraction (EBSD), together with microhardness, bending, and tensile tests, were used to comprehensively analyze the resulting properties. The findings demonstrate a substantial enhancement in the wires' mechanical properties due to the SiC particles. Both tool rotation and tool force were varied during the experimental campaign. Notably, the reduction in porosity and grain refinement resulted in a 12.78 % increase in tensile strength and an 18.6 % improvement in microhardness compared to Al 6082 alloy extruded wires. Grain orientation analysis revealed a fully recrystallized microstructure with a weak texture. Furthermore, the study evaluated power consumption and surface roughness while assessing the feasibility of deposition, thereby highlighting the potential application of this technique in advanced additive manufacturing processes.

Multi-Response Optimization of Single Point Incremental Forming of Al 6061 Sheet Through Grey-Based Response Surface Methodology

The single point incremental forming process (SPIF) is materialized to form the desired shapes in low-cost sheet metal processing and well suited for low batch components and customized designs. Many modifications have been attempted in recent years to maximize the formability, geometric accuracy and quality of the SPIF formed parts. In this work, an attempt has been made to analyse the influence of process parameters namely ball tool diameter, step size, spindle speed and sheet thickness on final wall thickness, forming force and surface roughness. The optimized results exhibit the desirable formability when the roller ball tool diameter of the tool is 12 mm. The results also project that formability of the sheet metal is minimized when the spindle speed is increased and the ball diameter maximizes the accuracy and surface roughness. Also minimizing the step size increases the product quality features. Upon conducting this multi-response optimization by grey based response surface methodology (RSM) technique It is identified that 12 mm ball diameter of the tool, 0.25 mm step size, 2445 rpm spindle speed, and 2 mm sheet thickness are the obtained optimized SPIF process parameters as confirmed through confirmation experiments.

Experimental and kinetic study of methanol/ethanol assisted oxidative degradation of ammonia in supercritical water

Ammonia is a refractory intermediate during supercritical water oxidation (SCWO) of nitrogen-containing wastes, and alcohols are usually introduced as auxiliary fuels to accelerate its degradation. The kinetics of methanol/ethanol assisted oxidative degradation of ammonia in supercritical water have been investigated in a flow reactor, covering alcohol-to-ammonia ratios of 0.2–2.0. During SCWO of ammonia-methanol mixtures, ammonia was mostly converted to N2, with N2O as the main by-product. Increasing methanol concentration facilitated effectively the degradation of ammonia. For the cases with ethanol assistance, high concentrations of HCN were detected at the investigated temperature. Increase in ethanol concentration enhanced ammonia conversion, but had a non-monotonic influence on N2 production. A detailed chemical kinetic model was developed by integrating the nitrogen chemistry with methanol/ethanol mechanisms. The model performance was further validated by comparing to the present and literature data. The model reproduced the ammonia conversions at different conditions fairly well, but overpredicted the N2 yield and underpredicted the NO2 and HCN yields slightly. Based on the model, reaction mechanism was inferred and important elementary steps were identified through kinetic analyses. Finally, the influence of process parameters on ammonia degradation rate was numerically explored. This study is expected to facilitate the application of SCWO technology for N-containing wastes treatment.

Study of ship-based carbon capture optimization considering multiple evaluation factors and main engine loads

Ship-Based Carbon Capture (SBCC) technology presents a promising approach to reduce greenhouse gas emissions in the marine transportation. Solvent-based carbon capture has emerged as a leading technology for SBCC, primarily due to its low retrofit costs and effectiveness in treating flue gas with low carbon content. However, challenges remain in optimizing system operation efficiency under the variable conditions of ship main engine loads and in understanding the mechanisms by which process parameters influence key evaluation factors. Consequently, this study established a pilot-scale experimental platform for solvent-based SBCC and developed a carbon capture model based on it. The influence of process parameters, such as main engine exhaust flow rate and liquid/gas ratio (L/G), on the evaluation factors was thoroughly explored. With the utilization of Shapley Additive Explanations (SHAP) analysis to quantify the influence of process parameters on the evaluation factors, a multi-objective optimization equation is proposed. The combination of machine learning and optimization algorithms offers an efficient approach for determining the optimal process of the SBCC system under different main engine loads. The research results show that the main engine exhaust flow rate is the most important process parameter affecting the carbon capture rate (CR), with an influence ratio as high as 64.33%. As the main engine exhaust flow rate increases, the maximum CR decreases from 97.84% to 61.13%. Although the extreme value of the regeneration energy consumption (REC) also decreases from 6.66 to 4.42 GJ/t CO2, the solvent flow rate's influence on REC is also significant, with influence ratios of 38.49% and 35.53%, respectively. A data-driven approach examined the optimal operating conditions at eight main engine loads, achieving a carbon capture rate prediction error of only 1.42% and a maximum REC error of only 0.55 GJ/t CO2. This study provides essential guidance for assessing the suitability of SBCC systems.

Review of Metal Screw Extrusion: State of the Art and Beyond

Metal screw extrusion (MSE) is a continuous, solid-state forming method utilizing an inherently high degree of deformation to consolidate fragmented input materials into a solid bulk by breaking their oxide skins. Severe plastic deformation with equivalent strain in the range of 10–20 can be achieved depending on set process parameters. Rigorous mixing can be employed to form sophisticated materials like bulk composites, nanocomposites, particle-reinforced metals, and fine-grained materials. Furthermore, the inherent solid-state processing is well suited for recovery of difficult-to-recycle materials. A range of non-ferrous materials has been manufactured by MSE and further characterized in terms of microstructural evolution and mechanical and functional properties. Furthermore, MSE has been studied in terms of flow, accumulated strain, and environmental impact. The following review aims to critically highlight the existing work performed on MSE, compare it to existing and emerging technologies as well as explore future development and possible applications. MSE has the potential to be utilized for numerous commercial applications. To realize industrial use of MSE, key aspects of the process and the influence of processing parameters on the resulting product must be understood.

Influence mechanism of magnetron sputtering process parameters on diamond surface preprocessing interface for chip heat sink

The interface between diamond and aluminum is poor in wettability and solid solubility. The interface bonding can be improved effectively by plating metal elements on diamond surface combined with heat treatment. In this paper, the influence of adjustable process parameters on the quality of Mo layer modified by magnetron sputtering was studied based on orthogonal experiments, and Mo-coated diamond/aluminum composite materials were prepared by Spark Plasma Sintering (SPS). The results indicate that the deposition of Mo layer on the diamond surface proceeds through three stages: adsorption, surface diffusion, and stable nucleus growth, forming an initial thin film, followed by layer-by-layer stacking through repeated growth of these stages. Sputtering time and sputtering pressure are the main factors affecting the quality of the coating. Mo layers prepared under conditions of 30 min and 0.5 Pa exhibit uniform and dense surface and moderate thickness. After heat treatment, recrystallization forms equiaxed grains, and Mo2C is formed in reaction with diamond, effectively enhancing the interface bonding strength between diamond and aluminum. The thermal conductivity of the diamond/aluminum composite material reached 342 W/(mK).