Optimal Process Parameters Research Articles

Optimizing 3D Laser Foil Printing Parameters for AA 6061: Numerical and Experimental Analysis

Abstract This study utilizes a technology known as 3D laser foil printing (LFP) to create precise structures by layering metal foils using laser welding. Metal foils have the advantages of rapid cooling and efficient heat conduction, allowing for the formation of fine-grained structures. However, when dealing with materials like aluminum alloys in laser processes, defects can arise as a result of their high reflectivity. To address this challenge, laser circular oscillation welding (LCOW) is applied to the LFP process. LCOW's circular motions with higher scanning frequencies widen the keyholes and reduce some defects such as spattering, bubble formation, and microcracks. Simulation predictions with an error margin of approximately 10% in comparison to experimental results demonstrate the reliability of the model. Furthermore, the study integrates circular packing design with artificial neural networks to create comprehensive processing maps tailored to different criteria for extracting optimal welding parameters. As a result, for the optimized processing parameters screened using the above systematic process, no cracks were observed on the upper surface of the 3D LFP parts produced with a laser power of 800 W and a scanning speed of 550 mm/s, and only 0.12% porosity was observed from the cross section of the sample. Future research will focus on incorporating simulation results to model microstructures more precisely and continually refining LCOW parameters as new materials and technologies emerge, ensuring the ongoing enhancement of weld quality in the 3D LFP process.

Artificial Neural Network for Benchmarking the Dimensional Accuracy of the PLA Fused Flament Fabrication Process

Fused Deposition Modeling (FDM) is an additive manufacturing technique that uses a 3D printer to extrude molten filament through a nozzle, which moves along the X, Y, and Z axes to create parts with the desired geometry. FDM offers numerous advantages, especially for producing parts with complex shapes, due to its ability to enable rapid and cost-effective manufacturing compared to traditional methods. This study implemented an Artificial Neural Network (ANN) to optimize process parameters aimed at minimizing dimensional inaccuracies in the FDM process. Key parameters considered for optimization included the number of shells, infill percentage, and nozzle temperature. The ANN utilized three algorithms: Scaled Conjugate Gradient, Bayesian Regularization, and Levenberg-Marquardt. Model performance was evaluated based on dimensional deviations along the X and Y axes, with a hidden layer of 25 neurons. Among the algorithms, Scaled Conjugate Gradient provided the most accurate results in minimizing dimensional errors.

Experimental investigation on in-situ laser-assisted mechanical ruling of single crystal silicon

Abstract In this paper, response surface methodology (RSM) was employed as a robust and convenient predictive tool to establish the correlation between process parameters of in situ laser-assisted mechanical ruling and the ductile-to-brittle transition of single-crystal silicon. The interaction effects among three factors laser power, ruling speed, and negative rake angle on the ductile-to-brittle transition of single-crystal silicon were investigated. The optimal combination of process parameters was determined to be a laser power of 30W, a ruling speed of 0.25 mm s−1, and a negative rake angle of 58°. Utilizing a self-assembled setup and the optimal process parameters, multiple processing experiments were conducted. The average error between the experimental and predicted values was found to be 2.8%.

Classification-Based Parameter Optimization Approach of the Turning Process

The turning process is a widely used machining process, and its productivity has a significant impact on the cost and profit in industrial enterprises. Currently, it is difficult to effectively determine the optimum process parameters under complex conditions. To address this issue, a classification-based parameter optimization approach of the turning process is proposed in this paper, which aims to provide feasible optimization suggestions of process parameters and consists of a classification model and several optimization strategies. Specifically, the classification model is used to separate the whole complex process into different substages to reduce difficulties of the further optimization, and it achieves high accuracy and strong anti-interference in the identification of substages by integrating the advantages of an encoder-decoder framework, attention mechanism, and major voting. Additionally, during the optimization process of each substage, Dynamic Time Warping (DTW) and K-Nearest Neighbor (KNN) are utilized to eliminate the negative impact of cutting tool wear status on optimization results at first. Then, the envelope curve strategy and boxplot method succeed in the adaptive calculation of a parameter threshold and the detection of optimizable items. According to these optimization strategies, the proposed approach performs well in the provision of effective optimization suggestions. Ultimately, the proposed approach is verified by a bearing production line. Experimental results demonstrate that the proposed approach achieves a significant productivity improvement of 23.43% in the studied production line.

Experimental analysis on fiber diameter of spunbond nonwoven fabrics through Plackett–Burman and Box–Behnken designs and its impact on mechanical properties

AbstractThe COVID‐19 pandemic sparked a surge in demand for nonwoven protective materials, prompting a significant increase in nonwoven fabric production. To advance understanding, particularly in the Spunbond process, we conducted experiments to analyze the effects of various input parameters on fiber diameter, and mechanical tests to study how fiber diameter influences the mechanical properties of spunbond nonwoven fabrics. Employing Plackett–Burman design and Box–Behnken design with Minitab 18, we have examined different process parameters and study the cause‐and‐effect relationships between input parameters and the response. A set of experiments were carried out with nine varying parameters, including polymer melt index, initial polymer temperature, and air velocity. By regression modeling, we assessed the effects and interactions of these factors on fiber diameter. The Box–Behnken approach revealed that only three factors significantly influenced fiber diameter. Our analysis unveiled valuable insights for optimizing process parameters to achieve a target fiber diameter of 31.0 μm, crucial for enhancing nonwoven fabric production. Moreover, the results of the tensile property tests show that fiber diameter influence mechanical properties of nonwoven fabrics. As the fiber diameters increase, the mechanical properties of the nonwoven fabric are increased.Highlights Market research of textile industry, particularly of nonwoven sector. Identification of the parameters of the Spunbond process. Selection of Placket–Burman and Box–Behnken designs to analyze, optimize, and predict fiber diameter. Evaluation of the designs results (analysis of variance, Pareto, Regression model …), determination of the optimal conditions and the factors that has most effect on fiber diameter. Investigation of the effect of fiber diameter on mechanical properties.

Metal Acetate-Enhanced Microwave Pyrolysis of Waste Textiles for Efficient Syngas Production

The production of waste textiles has increased rapidly in the past two decades along with the rapid development of the economy, the majority of which has been either landfilled or incinerated, resulting in energy loss and environmental pollution. Microwave pyrolysis, which can transform heterogeneous and complex waste feedstocks into value-added products, is considered one of the most competitive technologies for processing waste textiles. However, achieving selective product formation during the microwave pyrolysis of waste textiles remains a significant challenge. Herein, sodium acetate, potassium acetate, and nickel acetate were introduced into waste textiles through an impregnation method as raw materials to improve the pyrolysis efficiency. The optimized process parameters indicated that nickel acetate had the most favorable promotional effect of the three acetates. Notably, the waste textiles containing 1.0% Ni exhibited the highest gas production rate, with the hydrogen-containing combustible gas reaching 81.1% and 61.0%, respectively. Using X-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy to characterize the waste textiles before and after pyrolysis, it was found that nickel acetate was converted into metallic nickel (Ni0) during microwave pyrolysis. This active site significantly enhanced the pyrolysis process, and as the gas yield increased, the disorder of the resulting pyrolytic carbon also rose. The proposed Ni0-enhanced microwave pyrolysis mediated by nickel acetate offers a novel method for the efficient disposal and simultaneous resource recovery of waste textiles.

Enrichment, Antioxidant and Enzyme Inhibition Activities of Flavonoids from Artemisia Selengensis Turcz.

Macroporous resin was used to enrich flavonoids in the ethyl acetate extract of Artemisia Selengensis Turcz. Based on a single factor experiment, the enrichment process was optimized using the response surface method. The optimal parameters of the enrichment process were a sample concentration of 0.3 mg/mL, a loading rate of 1 mL/min, an elution flow rate of 2 mL/min, and a total flavonoid content of 155.38 ± 0.97 mg/g. The flavonoids enriched by AB-8 macroporous resin demonstrated significant scavenging activities against DPPH, ABTS+, and hydroxyl free radicals, and also exhibited certain inhibitory effects on α-amylase and α-glucosidase. Among them, the scavenging ability of the flavonoids enriched by AB-8 macroporous resin on hydroxyl free radical (IC50 = 30.31 ± 1.92 μg/mL) was the closest to Vc, and the inhibitory effect on α-glucosidase (IC50 = 16.19 ± 1.35 μg/mL) was the best. These findings confirmed the potential of Artemisia Selengensis Turcz. is a natural antioxidant and hypoglycemic drug.

Optimization of process parameters for polishing aero-engine blade with abrasive cloth wheel considering spindle vibration and polished roughness

The vibration of machine tool spindle is very important for machining. Firstly, in order to explore the relationship between spindle vibration and process parameters, the spindle vibration acceleration when polishing aero-engine blade was measured, and the quadratic polynomial models between the spindle vibration acceleration in X, Y and Z direction and the process parameters were established. Secondly, a quadratic polynomial model for the influence of process parameters on polished surface roughness was also determined. Thirdly, through the Analysis of Variance (ANOVA) and main effect analysis, it can be seen that the spindle speed has the greatest impact on the vibration. Finally, a multi-objective optimization model was established with the optimization objective of minimizing spindle vibration acceleration and polished surface roughness, and the optimal process parameters were solved using genetic algorithm. The optimal process parameters were verified and the results show that the polished surface roughness with the optimal process parameters are all less than 0.4 μm, and the deviation rates between the theoretical optimization results of spindle vibration acceleration and the experimental results are all less than 10%, indicating that the optimization results are good.

Validation of the technological process for the production of riamilovir-based solution for aerodispersible administration

BACKGROUND: An important step in the production of riamilovir-based solution for inhalation administration is the validation of critical stages of the technological process. First, a detailed study of all production steps, from the preparation of the initial ingredients to the final packaging, is carried out. Control tests are then conducted, including measuring key process parameters and analyzing the physical and chemical properties of the solution. One of the important aspects of process validation is also the training of production personnel. Proper understanding and adherence to all process instructions and requirements ensures that the process is followed correctly. AIM: Carry out validation activities throughout the stages of the technological process for the production of a solution for inhalation administration based on the active substance “riamilovir”. MATERIALS AND METHODS: The study was carried out using the developed Pilot Industrial Regulations for the production of the medicina. The quality assessment of pharmaceutical substances, excipients and pilot samples was carried out in accordance with the requirements of the State Pharmacopoeia of the Russian Federation and GMP rules. RESULTS: It has been established that the technological scheme for the production of a solution based on the active substance “riamilovir” contains 6 main stages. The greatest risk is observed at the following stages: Auxiliary work 3. Obtaining water — risk of bacterial contamination. Тechnological process 4. Preparation and sterilizing filtration of the solution — risks of insufficient concentration and unsterility of the solution. Тechnological process 5. Dosing the solution into vials is a risk due to underfilling, as well as violation of sterility. CONCLUSION: Validation of the technological process of production of solution for inhalation administration based on the active substance “riamilovir” has been carried out. Critical stages in the technological production process have been identified. The optimal parameters of the technological process have been determined and documented, leading to a predictable result — the release of a high-quality and safe drug.

Optimizing Hot Forging of 38MnSiVS5 Steel: A Multi-Objective Approach with Grey-Fuzzy Method

The present research focuses on the hot forging of 38MnSiVS5 micro-alloyed steel, examining the impact of key process variables, such as working temperature, deformation percentage and rate of cooling on mechanical properties, notably the ultimate tensile strength and impact energy. To optimize the process, Taguchi's parametric design, utilizing an orthogonal array in combination with grey relational analysis and fuzzy logic analysis, has been implemented. By applying grey-fuzzy logic analysis, the optimization of complex multiple responses is streamlined into a single grey-fuzzy reasoning grade. The study employs the Grey fuzzy logic method to concurrently optimize both responses. The grey-fuzzy reasoning grade serves as a performance index, aiding in the determination of the optimal process parameter settings for both the ultimate tensile strength and impact energy responses simultaneously.

Experimental investigation and optimization of process parameters on tensile strength of carbon coated PLA material

Abstract This study explores the effect of key process parameters on the tensile strength of carbon-coated PLA (Polylactic Acid) material using additive manufacturing. The problem addressed is the need to enhance the mechanical properties of PLA, a widely used biodegradable polymer, by optimizing process parameters to improve its tensile strength when coated with carbon. The parameters investigated include infill pattern, printing speed, layer thickness, and orientation. A response surface methodology (RSM) was employed to design the experiments, while Minitab 15 software was used to analyze the data through analysis of variance (ANOVA). The results indicate that the optimal process parameters, linear infill pattern, printing speed of 20 mm/s, layer thickness of 150 µm, and Y-90 orientation, yield an average tensile strength of 56.4 MPa. A regression model was developed to predict tensile strength, with a high degree of accuracy (R² = 0.97). Confirmation tests verified the model’s predictions, contributing to the development of high-performance PLA-based materials for demanding applications.

Investigation of laser sintering process parameters for anode foils in aluminium electrolytic capacitors considering temperature distribution

Abstract The anode foil is a critical component of aluminium electrolytic capacitors, with its performance directly impacting the overall quality of the capacitors. Currently, sintered anode foil with excellent bending resistance and high specific capacitance is considered an ideal material for capacitor manufacturing; however, research on its optimal sintering parameters remains insufficient. In this study, a three-dimensional temperature field model is developed within the Comsol Multiphysics (6.0) environment, accounting for the temperature dependence of aluminium. By varying laser power and scanning speed, the temperature distribution along the laser scanning trajectory is determined, facilitating the identification of optimal process parameters for laser sintering anode foils in electrolytic capacitors. Subsequent laser sintering experiments validate the accuracy of these parameters. The findings indicate that the peak temperature of the molten pool rises with increased laser power and decreased scanning speed. The optimal process parameters for laser sintering anode foils in electrolytic capacitors are a powder layer thickness of 50 µm, a laser power of 140 W, and a scanning speed of 0.05 m/s. The specific capacitance of laser-sintered anode foil, formed at voltages of 375 V and 520 V, ranges from 0.847 to 1.157 μF/cm² and 0.717 to 0.935 μF/cm², respectively, when the particle size is between 3 and 4 μm. A specific capacitance of 0.733 μF/cm² can be achieved, which meets the performance requirements for aluminium electrolytic capacitors.

Optimization of FDM 3D Printer Process Parameters to Minimize Dimensional Errors with PLA Material Using Response Surface Methodology

This paper presents a response surface methodology to fit a second-order response surface model aimed to finding process parameters to minimize length error (LE) and diameter error of the cylindrical shafts (DE) in fused deposition modeling (FDM) using polylactic acid (PLA) material. The process parameters in this study included layer height (LH), which varied from 0.1 to 0.4 mm, and print speed (PS), which ranged from 20 to 60 mm/s, while other parameters were set to constant values. The results showed that optimal process parameters obtained in this study significantly lower dimensional errors than the initial parameterization recommended by UltiMaker Cura software.

Optimization of Extraction Process, Structure Characterization, and Immunomodulatory Activity of Polysaccharides from Black Garlic

AbstractUltrasound assisted extraction (UAE) was used to extract polysaccharides from black garlic, and the extraction process for UAE of black garlic polysaccharides (BGPs) was optimized via RSM coupled with genetic algorithm. The optimal extraction process parameters were obtained as follows: extraction time of 30 min, liquid‐to‐solid ratio of 29 mL/g, extraction temperature of 51 ℃, and ultrasound power of 418 W, and the yield of BGPs was 10.17% ± 0.14%. Subsequently, the crude BGPs were further purified by DEAE‐52 cellulose and Sephadex G‐100 to obtain a homogeneous fraction (BGPs‐1‐SG with the molecular weight of 1.37 × 106 Da) that was comprised of mannose (Man), glucuronic acid (GlcA), rhamnose (Rha), glucose (Glc), and fucose (Fuc) with a molar ratio of 40.23:71.06:2.96:85.38:7.32. Congo red and circular dichroism spectroscopy indicate that BGPs‐1‐SG has a triple helix structure. Scanning electron microscope and atomic force microscope demonstrate that BGPs‐1‐SG showed irregular structures including sheet‐like, rod‐shaped, irregular spherical structures, and aggregated in aqueous solutions. Moreover, BGPs‐1‐SG could increase viability, phagocytic rate, and NO content of RAW264.7 cells. Furthermore, BGPs‐1‐SG could promote the secretion and mRNA expression levels of IL‐1β, IL‐6, and TNF‐α. The findings can provide an important reference for the development of functional foods.

Optimizing processing parameters to produce a novel spray dried hydrolyzed rice-derived ingredient using response surface methodology

Optimizing processing parameters to produce a novel spray dried hydrolyzed rice-derived ingredient using response surface methodology

Optimizing laser cladding process parameters for transformation-induced plasticity FeMnCoCr high entropy alloy: A multi-objective approach

A multi-objective optimization approach utilizing the response surface method (RSM) is proposed to determine the optimal processing parameters for laser cladding of Fe50Mn30Co10Cr10 coating. In this paper, a single-variable control method was employed to adjust the laser cladding parameters, and preliminary experiments were conducted to establish the optimization range for the RSM laser cladding parameters. A mathematical prediction model of input processing parameters (laser power, scanning speed and powder feed speed) and output response (dilution rate, W/H, microhardness and porosity) was established by the response surface method. The results indicated that both the dilution rate and microhardness had a positive correlation with laser power and scanning speed, while they were negatively correlated with the powder feed rate. The scanning speed is the most significant factor influencing the porosity of the coating, followed by the powder feed rate. The optimal processing parameters were identified as follows: laser power at 1750 W, scanning speed at 8.0 mm/s, and powder feed rate at 11.5 g/min. The model demonstrated strong agreement with the experimental results. The coating molding quality is exceptional, with an average porosity of 0.07 % and an average microhardness of 208.32 HV0.2. Meanwhile, the coating was composed of HCP phase and FCC phase, with the HCP phase comprising15.6 % and the FCC phase 84.4 %, respectively. Under the optimal processing parameters, the Fe50Mn30Co10Cr10 high-entropy alloy coating demonstrated impressive ductility and strength, with a deformation of 55.93 % and a compressive strength of 2153.7 MPa. The fracture mechanism of Fe50Mn30Co10Cr10 coatings is transcrystalline fracture and toughness fractures.

Study on heat transfer and flow of molten pool during the deposition process of laser wire additive manufacturing

In the laser wire additive manufacturing process, the molten pool acts as the critical link between the wire and the deposited part. The heat transfer and flow behavior within the molten pool predominantly determine the quality of the final deposition. Under laser power ranging from 2400 to 3000 W, traverse speeds between 0.01 and 0.04 m/s, and wire feeding speeds from 0.03 to 0.08 m/s, three distinct flow states—single-swirl, double-swirl, and no-swirl—were observed with increasing heat input. Under the optimum process parameters, the molten pool with stable temperature distribution and orderly flow was obtained. In multilayer deposition, the implementation of a laser decay strategy mitigates steep temperature gradients, diminishes the Marangoni effect within the molten pool, and effectively reduces both heat accumulation and lateral flow. Consequently, the flow mode transitions from no-swirl to swirl, and the maximum flow velocity decreases by 40%.

KH571 construct interfacial molecular bridge in calcium silicate/TMPTA/HDDA scaffolds for improving mechanical properties, biodegradability and photopolymerization

Digital Light Processing (DLP) offers the potential for personalized bone implants. Within this method, the interfacial bonding capacity of inorganic/organic materials and the solid-phase content of the slurry emerge as primary factors influencing scaffolds mechanical properties. In this research, KH571 was applied to establish an interfacial “molecular bridge”, adopting in situ coupling technology to forge stable covalent bonds between calcium silicate (CSi) and KH571. Chemical grafting, surface photografting, and photopolymerization techniques were then utilized to construct a photo-crosslinked network by CSi-KH571-TMPTA/HDDA slurry, thereby transforming the weak physical connections at the interface into strong chemical bonds. Consequently, the curing capacity and mechanical properties of the scaffolds were enhanced. Further control grain size, crystal phase transition, and shrinkage of CSi-KH571 scaffolds, post-treatment sintering processes were employed, resulting in scaffolds with a high content of β-CSi. Moreover, the optimal process parameters were selected concerning grafting rate, chemical composition, microscopic morphology, crystalline transformation, dimensional accuracy, mechanical properties, biodegradability and biocompatibility of CSi-KH571. The elastic modulus and compressive properties of CSi25-55 scaffolds exhibited a notable improvement of 29.71 % and 59.30 %, respectively, compared to CSi-50 scaffolds. By regulating the phase composition of CSi, CSi25-55 scaffolds were designed to possess a controllable degradation. In vitro cell culture experiments validated its excellent biocompatibility and promoted the proliferation and differentiation of bone marrow mesenchymal stem cells (BMSCs) as well as the deposition of bone matrix. Herein, a novel and sustainable approach has been promoted for enhancing the interfacial bonding capacity of inorganic/organic materials and the solid-phase content of printing slurry, which lays the foundation for the printing of high-resolution degradable bioceramic scaffolds.

Research on machining technology of stepped boring for intersecting holes in aircraft

Abstract During the assembly process of a large-scale aircraft fuselage, critical bearing areas require the drilling of intersecting holes, which are commonly processed using traditional single-edged reamers by most domestic manufacturers. To improve the efficiency and accuracy of the finishing process for these holes, enhance the quality of the assembly, and further shorten the construction cycle for precision processing, improvements need to be made to traditional single-edge reamer machining methods. This paper proposes a new approach that uses stepped reamers to machine intersecting holes. By setting up an experimental platform to simulate actual processing conditions and optimize processing parameters, the study analyzes and compares the quality and efficiency of traditional reaming and stepped reaming modes. The results show that stepped reaming can improve processing efficiency by 50.6% compared to traditional machining while also reducing human intervention and minimizing quality risks. The findings from this research project can be extended to various aircraft fuselages or wings for precise drilling of intersecting holes, providing significant guidance for efficient and high-quality delivery of aircraft.

Jet cavitation-enhanced hydration method for the preparation of magnesium hydroxide

During the preparation of magnesium hydroxide via the hydration method, in-situ growth and agglomeration often inhibit the reaction. This study used active magnesium oxide as the raw material and employed jet cavitation technology to enhance the hydration process. Based on the growth process of magnesium hydroxide, the mechanism of jet-enhanced hydration was analyzed. The effects of reaction temperature (T), reaction time (t), solid-liquid ratio (s), and cavitation number (σ) on the hydration rate were investigated. An L25(54) orthogonal experiment explored the significance of each factor's impact on the hydration rate. The hydration products were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), and a specific surface area analyzer. Results indicate that the factors affecting the hydration rate, in order of significance, are cavitation number > reaction temperature > solid-liquid ratio > reaction time. The optimal process parameters were determined to be a reaction temperature of 70 °C, reaction time of 80 min, solid-liquid ratio of 1:12, and cavitation number of 0.42. Under these conditions, the hydration rate reached 94.87 %, producing well-dispersed lamellar magnesium hydroxide with a narrow particle size distribution (median particle size D50 = 4.511 μm) and a BET specific surface area of 11.345 m²/g.