Optimization Of Process Parameters Research Articles

Optimization of process parameters of catalytic pyrolysis using natural zeolite and synthetic zeolites on yield of plastic oil through response surface methodology

Optimization of process parameters of catalytic pyrolysis using natural zeolite and synthetic zeolites on yield of plastic oil through response surface methodology

Physicochemical Investigations of Textile Wastewater and Process Parameter Optimization for Bio-decolorization of Congo Red Dye by Pseudomonas aeruginosa MT-2 Strain

Pollution caused by dyes is a major environmental threat, posing adverse impacts on humans, animals, and plants. Therefore, the remediation of such pollutants is essential to protect the environment. This study aimed to conduct physicochemical and bacteriological analyses of textile wastewater to isolate and identify potential native bacterial strains for the decolorization of Congo red dye. Physical and nutritional process parameters were optimized to achieve maximum decolorization. The biological and chemical oxygen demands of the analyzed textile waste water were found to be above the recommended limits. In this study, 19 Congo red -decolorizing bacteria were isolated, with one bacterial culture capable of growing at a higher dye concentration of 300 mg/L. This bacterium was characterized biochemically and genetically (using 16S rRNA sequencing) and identified as the Pseudomonas aeruginosa MT-2 strain. A maximum decolorization of 94.0% was achieved at an initial dye concentration of 150 mg/L, 35°C, and pH 8.0 under static conditions. The bacterial culture also showed resistance to heavy metals such as arsenic, lead, and chromium. The biodegradation of Congo red dye was confirmed through UV-vis spectral analysis and Fourier transform infrared spectrophotometry. The findings of this study demonstrate the high remediation potential of the MT-2 strain, making it suitable for possible use in dye biodecolorization at contaminated sites.

Optimization strategy of computer numerical control machining process parameters in biomanufacturing mold

With the rapid development of biomanufacturing technology in the medical and pharmaceutical fields, the demand for high-precision and high-quality molds has surged. When Computer numerical control (CNC) machining biomanufacturing molds, the optimization of process parameters becomes the key to improve efficiency and quality. The purpose of this study is to explore the optimization strategy of CNC machining process parameters to achieve the best surface quality, dimensional accuracy and machining efficiency. Through literature review, the spindle speed, feed speed and cutting depth are selected as the key parameters, and the multi-objective optimization model is constructed by response surface method, which is solved by genetic algorithm. The experiment shows that the process parameters of CNC system in mold manufacturing are cutting speed 100 (m/min), feed rate 0.2 (mm/rev) and cutting depth 0.5 (mm), which will effectively reduce the manufacturing cost, and effectively control the alarm times within 35 times in different processing equipment, greatly reduce the risk. The optimization strategy can significantly improve the surface quality and productivity of the mold and reduce the cost. The comparative analysis verifies the effectiveness of the method, which provides new theoretical and technical support for CNC machining in the field of biomanufacturing.

Process Parameters Optimization of Laser Cladding for HT200 with 316L Coating Based on Response Surface Method

Process Parameters Optimization of Laser Cladding for HT200 with 316L Coating Based on Response Surface Method

Optimization of Laser Based-Powder Bed Fusion Parameters for Controlled Porosity in Titanium Alloy Components

Laser based-powder bed fusion (LB-PBF) enables fast, efficient, and cost-effective production of high-performing products. While advanced functionalities are often derived from geometric complexity, the capability to tailor material properties also offers significant opportunities for technical innovation across many fields. This study explores the optimization of the LB-PBF process parameters for producing Ti6Al4V titanium alloy parts with controlled porosity. To this end, cuboid and lamellar samples were fabricated by systematically varying laser power, hatch distance, and layer thickness according to a full factorial Design of Experiments, and the resulting specimens were thoroughly characterized by analyzing envelope porosity, surface roughness and waviness, surface morphology, and surface area. A selection of specimens was further examined using small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS) to investigate the atomic structure and nanometric porosity of the material. The results demonstrated the possibility to finely control the porosity and surface characteristics of Ti6Al4V within specific LB-PBF process ranges. The pores were found to be mostly closed even for thin walls, while the surface roughness was recognized as the primary factor impacting the surface area. The lamellar samples obtained by exposing single scan tracks showed nearly an order-of-magnitude increase in both surface area and pore volume, thereby laying the groundwork for the production of parts with optimized porosity.

Enhancing Mechanical Properties of Additively Manufactured H13: A Two-Step Approach Integrating Processing Parameters Optimization and a Tailored Heat Treatment

Enhancing Mechanical Properties of Additively Manufactured H13: A Two-Step Approach Integrating Processing Parameters Optimization and a Tailored Heat Treatment

Optimizing energy consumption in post-combustion CO2 capture at an NGCC power plant: a simulation-based approach

Abstract This study aims to optimize energy consumption in post-combustion carbon capture processes at a Natural Gas Combined Cycle (NGCC) power plant. It further addresses challenges associated with steam extraction from NGCC power plants and explores non-condensable steam turbines to boost process efficiency. Various scenarios are explored to minimize energy requirements by leveraging heat integration and alternative solvent compositions. The research uses simulations with commercially available software and literature-derived data to address the challenges of high energy consumption in such processes. Emphasis is placed on optimizing solvent composition and implementing advanced heat optimization strategies to reduce energy consumption. Four scenarios with different solvent compositions are investigated, utilizing Monoethanolamine and aqueous piperazine. The results show that process parameter optimization and heat optimization strategies can result in significant energy savings. To attain a carbon-neutral energy landscape, this research helps develop more sustainable and effective carbon capture methods.

Optimization of process parameters of electron beam welded Nimark 300 for weld bead analysis

Electron beam welding (EBW) offers an excellent capability of introducing the desired weld properties in similar and dissimilar welds. The high depth-to-width ratio enables exceedingly concentrated attention to the weld area, resulting in a smaller HAZ, making it one of the finest welding techniques. This study thus optimizes the basic input parameters of the machine based on weld quality, which incorporates weld penetration and geometry. The EBW was performed on Maragine steel (Nimark 300), a given alloy widely utilized in aerospace sensing applications. In analyzing the input variables associated with machining, this research employed the Taguchi optimization tool by zeroing in weld penetration and geometry. Then, variance analysis (ANOVA) was used for further study. Lastly, we conducted a verification test to compare the experimental results with the theoretically predicted values and thoroughly scrutinized the mathematical modelling. The machine parameters as voltage were 40, 50 and 60 KV, and the welding current was selected as 2, 4 and 6 mA. The welding speed for joining was chosen as 300, 600 and 900 mm/min. The maximum penetration was obtained at 50KV, 6mA current and 300 mm/min. The maximum bead width (BW) was obtained at 60 KV, 6 mA and 600 mm/min.

Optimization of Briquetting Process Parameters for Rice Straw Biofuels

The optimization of briquetting process parameters for producing biofuels from rice straw, a widely available agricultural waste. By systematically varying key parameters such as pressure, temperature, and moisture content, we aimed to enhance the physical and thermal properties of the briquettes. Through experimental design and statistical analysis, we identified optimal conditions to maximize briquette density and calorific value while minimizing ash content. The findings show that optimized briquetting greatly enhances the efficiency and potential of rice straw as a renewable energy source, providing a sustainable alternative to traditional fuels. This research contributes to advancing biofuel production technologies and promoting the utilization of agricultural waste for energy generation. Briquetting technology has great potential to transform waste biomass in affordable, effective and environmentally safe, high-quality solid fuel for households and industry use. This study focuses on optimizing the briquetting process for rice straw to enhance its quality as a biofuel. Key parameters, including compaction pressure, moisture content, binding agent type, and particle size, were systematically varied to improve density, durability, hardness, calorific value, and reduce ash content. Results indicate significant improvements in briquette performance, with calorific values increasing to 17.5 MJ/kg and ash content reducing to 4%. Optimized briquettes offer enhanced mechanical strength and combustion efficiency, positioning rice straw briquettes as a viable, eco-friendly alternative to traditional fossil fuels, contributing to sustainable energy and agricultural residue management.

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.

Microstructural analysis of Inconel 718 manufactured via direct energy deposition: response surface methodology for process parameters optimisation and post-heat treatment

Microstructural analysis of Inconel 718 manufactured via direct energy deposition: response surface methodology for process parameters optimisation and post-heat treatment

Comprehensive study on statistical methods for optimization of process parameters and material properties of AlSi10Mg in laser powder bed fusion

This study provides a systematic investigation of the effects of process parameters and heat treatments on the material properties of AlSi10Mg, produced by laser powder bed fusion (L-PBF). Using a central composite design (CCD) with 106 test specimens (49 cubes, 57 tensile), the samples were studied for key properties: density (up to 99.96%), hardness (up to 154.6 HV1), surface roughness (as low as 1.9 Ra), tensile strength (up to 487.5 MPa), and elongation at break (up to 16.6%). Statistical analysis (ANOVA) identified laser power and scanning speed as the most influential parameters on these properties. Additionally, heat treatment was shown to reduce hardness and tensile strength but increase elongation at break, demonstrating the ability to modify mechanical properties based on the desired outcome. Process parameter optimization yielded properties comparable to some of the highest reported values for AlSi10Mg in the literature. The study also discusses the transferability and reproducibility of L-PBF results across different machines, highlighting challenges related to machine-to-machine variations, lack of calibration and standardization and parameter consistency. The results demonstrate the potential of L-PBF to produce AlSi10Mg parts with tailored properties for industrial applications.

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.

Optimal Tungsten Inert Gas Welding Parameters of Dissimilar Aluminum Alloys Al 7075 and Al 6061 Using Ultrasonic Vibration and Nanocomposite Filler (Al 5356/ZrB2) to Alleviate Hot Cracking Phenomenon

Abstract In this study, the welding of dissimilar aluminum alloys, Al 7075 and Al 6061, was investigated using Al 5356 filler rods reinforced with ZrB2 particles. The welding process was conducted using tungsten inert gas (TIG) welding, with and without ultrasonic vibration, to enhance weld quality and reduce hot cracking. Optimization of process parameters for dissimilar TIG welding was performed through Response Surface Methodology (RSM), which generated a design matrix to analyze the influence of process parameters on response variables. Numerical and graphical optimization was applied to minimize hot cracking sensitivity and maximize microhardness. The RSM-based models suggested an optimal welding current of 93 A, the use of Al 5356/ZrB2 nanocomposite filler, and the application of ultrasonic vibrations. Experimental validation of the identified solution demonstrated improvements in weld quality, including increased yield strength and ductility. The combination of nano-reinforced fillers and ultrasonic vibrations was found to enhance weldability and mitigate hot cracking in dissimilar aluminum joints. The mechanism of hot cracking reduction involved grain refinement, degassing, and homogenization due to ultrasonic vibrations, as well as the modification of weld pool chemistry and control of dilution by the nanocomposite filler, which collectively minimized solidification shrinkage and stress. Under these optimized conditions, no hot cracking was observed experimentally.

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.

Optimizing laser-induced phase transformations in Sb2S3 thin films: Simulation framework and experiments

We present a novel simulation approach combined with pulsed laser experiments, spectroscopic ellipsometry, and Raman spectroscopy to comprehensively analyze phase transformation dynamics in thin films. The simulations apply to any thin film stack and incorporate critical factors, such as thin film interference, heat transfer, and temperature-dependent optical properties during heating and melting. As a case study, we investigate the picosecond laser-induced amorphization of antimony sulfide (Sb2S3) thin films, a promising alternative to traditional phase-change materials in photonic applications to validate the simulation model. The computational efficiency of our simulations enables not only the investigation of the laser-induced phase transformation but also the optimization of key process parameters and parameter fitting. The simulations identified optimal film thickness and laser fluence parameters that maximize energy efficiency, melting effectiveness, and quenching rate while ensuring high reflectivity contrast between the amorphous and crystalline states. By constructing a wide-ranging, high-resolution parameter map of the laser fluence and film thickness dependence of the melting process, we demonstrate how this model guides the understanding of phase transformation dynamics. Raman spectroscopy confirms the polycrystalline to amorphous transition of Sb2S3 and provides a semiquantitative estimate of the amorphous fraction as a function of laser fluence, which is qualitatively consistent with the simulation predictions of the model. The open-source simulation framework, experimentally validated, provides valuable insights into laser-induced amorphization dynamics in Sb2S3 and related phase-change material thin films, enabling rapid optimization of photonic devices.

Quality by design optimization of formulation variables and process parameters for enhanced transdermal delivery of nanosuspension.

This investigation aims to fabricate, characterize, and optimize organogel containing andrographolide nanosuspension to enhance transdermal drug delivery into and across the skinin vitro. We identified the critical material attributes (CMAs) and critical process parameters (CPPs) that impact key characteristics of andrographolide nanosuspension using a systematic quality-by-design approach. We prepared andrographolide nanosuspension using the wet milling technique and evaluated various properties of the formulations. The CMAs were types and concentrations of polymers, types and concentrations of surfactants, drug concentration, and lipid concentration. The CPPs were volume of milling media and milling duration. Mean particle size, polydispersity index, encapsulation efficiency, and drug loading capacity as critical quality attributes were selected in the design for the evaluation and optimization of the formulations. Furthermore, we developed and evaluated organogel formulation to carry andrographolide nanosuspension 0.05% w/w. Drug release and permeation studies were conducted to assess the drug release kinetics and transdermal delivery of andrographolide. We presented the alteration in the average particle size, polydispersity index, encapsulation efficiency, drug-loading capacity, and drug release among various formulations to select the optimal parameters. The permeation study indicated that organogel delivered markedly more drug into the receptor fluid and skin tissue than DMSO gel (n = 3, p < 0.05). This enhancement in transdermal drug delivery was demonstrated by cumulative drug permeation after 24h, steady-state flux, permeability coefficient, and predicted steady-state plasma concentration. Drug quantity in skin layers, total delivery, delivery efficiency, and topical selectivity were also reported. Conclusively, andrographolide nanosuspension-loaded organogel significantly increased transdermal drug delivery in vitro.

Multiscale model of material removal for ultrasonic assisted polishing of cylindrical surfaces

Ultrasonic assisted polishing is an effective and precise method in engineering production that applies in finishing surface. A multiscale model was developed which is able to forecast the surface micromorphology and material removal rate. Process factors were considered include polishing force, grain diameter, ultrasonic amplitude and so on in this model at different scales. The impact of various process factors on surface roughness and material removal rate were analyzed by orthogonal experimental table. The perfect combination of process parameters was identified, and its effectiveness was verified through both simulations and experimental analysis, with an error rate below 9.43%. To provide a mechanism study of ultrasonic polishing of curved surfaces and optimization of process parameters by this theoretical model.

Optimization of hydrogel extrusion printing process parameters based on numerical simulation

The printing quality of biological scaffold is not only affected by the fluidity of bio-ink but also by the printing process parameters, such as the size of the needle, printing height, extrusion speed, and printing speed. Therefore, optimizing the printing process parameters can further improve the molding quality of the biological scaffold. In this study, the printing and deposition process of sodium alginate hydrogel was modeled and analyzed based on the Herschel–Bulkley model by the finite element simulation method. The orthogonal experiment method, control variable method, and response surface method were used to design experiments, and the influences of different printing process parameters on the hydrogel deposition process were investigated. Finally, the optimal combination of printing process parameters was obtained by taking the molding degree and offset of the hydrogel line as optimization objectives. The results show that the strength relationship of the factors affecting the molding degree of the hydrogel line is as follows: printing height &amp;gt; needle diameter &amp;gt; printing speed &amp;gt; extrusion speed, and the strength relationship of the factors affecting the printing offset is as follows: printing height &amp;gt; needle diameter &amp;gt; extrusion speed &amp;gt; printing speed. The optimal combination of printing process parameters is d = 0.34 mm, H = 0.51 mm, v1 = 10 mm/s, and v2 = 7.91 mm/s. Compared with the printing experiment results of the hydrogel line molding degree under the optimal process parameters, the error range is within −11.55%–1.27%, which further demonstrates the reliability of the optimization method of hydrogel extrusion printing process parameters based on numerical simulation and response surface method.

Optimization of thermoplastic composites process parameters based on robotic fiber placement

Optimization of thermoplastic composites process parameters based on robotic fiber placement