Optimal Process Research Articles

Investigation of the Fermentation Process of Moringa oleifera Leaves and Its Effects on the Growth Performance, Antioxidant Capacity, and Intestinal Microbiome of Procambarus clarkii

Moringa oleifera is renowned for its high antioxidant activity. However, few studies have been conducted on its effects on aquatic animals. The aim of this experiment was to investigate the optimal fermentation process of M. oleifera leaves and to evaluate the effects of fermented M. oleifera leaves on crayfish (9.11 ± 0.3 g) in terms of growth performance, antioxidant capacity, and gut microbiological parameters. By optimizing the fermenting material/water ratio, fermentation time, temperature, and strain, the optimal fermentation conditions of a 10% water ratio + 48 h + 30 °C + inoculation with 2% B. amyloliquefaciens (107 CFU mL−1) were obtained. These conditions resulted in notable increases in the contents of the total protein, total phenols, flavonoids, and amino acids (p < 0.05) while also leading to a notable decrease in the content of tannins in contrast to those of unfermented M. oleifera leaves (p < 0.05). The fermented M. oleifera (FMO) leaves were incorporated at five concentrations, including 0% (control (CT)), 0.25% (0.25FMO), 0.5% (0.5FMO), 1% (1FMO), and 2% (2FMO). The results showed that the 1FMO group performed better in terms of the final body weight (FBW), weight gain rate (WGR), and specific weight gain rate (SGR) compared with the CT group (p < 0.05). In addition, amylase and lipase activities were significantly higher in the 1FMO and 2FMO groups compared with the other groups (p < 0.05). The fermented M. oleifera leaves significantly increased the catalase (CAT) activity in the crayfish (p < 0.05). The superoxide dismutase (SOD) activity was significantly increased in the 0.25FMO, 1FMO, and 2FMO groups, and the malondialdehyde (MDA) content was significantly decreased while the glutathione peroxidase (GSH-PX) content was significantly increased in the 0.5FMO, 1FMO, and 2FMO groups (p < 0.05). Furthermore, the 1FMO group was observed to significantly increase the abundance of Firmicutes while simultaneously reducing the abundance of Aeromonas (p < 0.05) and adjusting the structure of the intestinal microbiome. In conclusion, this study established the optimal fermentation conditions for M. oleifera and obtained a product with high nutrient and low tannin contents. Furthermore, the incorporation of 1% FMO was demonstrated to facilitate growth, enhance the antioxidant capacity, and optimize the gut microbiology in crayfish.

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.

Optimizing quality and cost in remanufacturing under uncertainty

AbstractIn the context of growing sustainability demands, businesses are increasingly adapting their production practices by integrating remanufacturing. However, companies often face challenges in profitably implementing remanufacturing due to complexities arising from uncertainties in processes, product quality, and market conditions. This highlights the need for effective decision support in remanufacturing processes. Addressing this challenge, our research introduces an algorithm designed to identify cost-efficient process plans that optimize order fulfillment while considering a company’s specific capabilities and inventory levels. By modeling the remanufacturing planning process as a Markov process, our algorithm comprehensively accounts for both process-related and quality-related uncertainties. This approach enables the evaluation of all Pareto optimal process plans in terms of cost efficiency and reliability. We validate our methodology through a real-world application in the automation industry, specifically focusing on the remanufacturing of variable speed drives. This case study demonstrates the practical relevance of our approach and a potential for significant cost reductions, enhanced process efficiency, and improved labor productivity. Overall, businesses gain critical insights into the financial prospects of their remanufacturing efforts, identifying opportunities for optimization and expansion into new product quality categories. This enhances their economic potential and aligns with consumer preferences for distinct product qualities.

Experimental Investigation on in-situ Laser-Assisted Mechanical Ruling of Single Crystal Silicon

Abstract In this study, 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 0.25mm/s, 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%.

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.

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.

Laser Directed Energy Deposition Additive Manufacturing of Al7075 alloy: Process Development, Microstructure, and Porosity

7xxx series aluminum alloys are priority materials adopted in aerospace because of their lightweight property and excellent mechanical performance. The combination of lightweight material and additive manufacturing techniques can significantly promote lightweight design in many industries. This study developed the optimal process for manufacturing Al7075 alloy by laser-aided directed energy deposition and revealed the material properties of the as-deposited Al7075 specimens. Firstly, single-track experiments were conducted by varying laser power, printing speed, and powder delivery rate in broad ranges. Results indicated that the printing speed and powder delivery rate impact the surface finish and shape of single-track beads considerably. Block specimens printed with the optimal parameters selected from the single-track experiments present crack-free quality and have a high relative density of up to 99.89%. Second phases with rich Cu, Mg, and Zn elements along the inter-dendritic regions and grain boundaries were observed from the microstructure inspection. The composition of zinc in the deposited samples is lower than usual, which leads to a relatively low microhardness.

Recovery of Barium, Nickel, and Titanium Powders from Waste MLCC

The development of the electronics industry has led to an increased demand for the manufacture of MLCC (Multilayer Ceramic Capacitors), which in turn is expected to result in a rise in MLCC waste. The MLCC contains various metals, notably barium, titanium, and nickel, whose disposal is anticipated to increase correspondingly. Recently, recycling technologies for electronic waste have garnered attention as they address waste management and raw material supply challenges. This paper investigates the recovery of barium, nickel, and titanium from the MLCC by a hydrometallurgical process. Using citric acid, which is an organic acid, the metal inside the MLCC was leached. Additionally, metal materials were recovered through precipitation and complexing processes. As a result, barium and titanium were recovered from the leachate of the waste MLCC, and 93% of the nickel-based powder was recovered. Furthermore, the optimal recovery process conditions for recycling these metal elements were investigated.

Metaheuristic optimized complex-valued dilated recurrent neural network for attack detection in internet of vehicular communications

The Internet of Vehicles (IoV) is a specialized iteration of the Internet of Things (IoT) tailored to facilitate communication and connectivity among vehicles and their environment. It harnesses the power of advanced technologies such as cloud computing, wireless communication, and data analytics to seamlessly exchange real-time data among vehicles, road-side infrastructure, traffic management systems, and other entities. The primary objectives of this real-time data exchange include enhancing road safety, reducing traffic congestion, boosting traffic flow efficiency, and enriching the driving experience. Through the IoV, vehicles can share information about traffic conditions, weather forecasts, road hazards, and other relevant data, fostering smarter, safer, and more efficient transportation networks. Developing, implementing and maintaining sophisticated techniques for detecting attacks present significant challenges and costs, which might limit their deployment, especially in smaller settings or those with constrained resources. To overcome these drawbacks, this article outlines developing an innovative attack detection model for the IoV using advanced deep learning techniques. The model aims to enhance security in vehicular networks by efficiently identifying attacks. Initially, data is collected from online databases and subjected to an optimal feature extraction process. During this phase, the Enhanced Exploitation in Hybrid Leader-based Optimization (EEHLO) method is employed to select the optimal features. These features are utilized by a Complex-Valued Dilated Recurrent Neural Network (CV-DRNN) to detect attacks within vehicle networks accurately. The performance of this novel attack detection model is rigorously evaluated and compared with that of traditional models using a variety of metrics.

Surface modification of fabrics using dielectric barrier discharge plasma for improved antifouling performance

Abstract Surface modification of fabrics is an effective way to endow them with antifouling properties while still maintain their key advantages like comfort, softness, and stretchability. Herein, an atmospheric pressure dielectric barrier discharge (DBD) plasma method is demonstrated for the processing of silk fabrics using 1H,1H,2H,2H-perfluorodecyltriethoxysilane (PFDS) as the precursor. The results showed the successful grafting of PFDS groups on the surface of silk fabrics without causing damage. Meanwhile, the gas temperature is rather low during the whole processing procedure, suggesting the non-equilibrium characteristics of DBD plasma. The influence of processing parameters on fabrics was systematically investigated, like the PFDS concentration, plasma treatment time, and plasma discharge power. An optimum processing condition was determined to be PFDS concentration: 8 wt%, plasma processing time: 40 s, and plasma power: 11.87 W. However, with the prolonged plasma processing time or enhanced plasma power, the plasma-grafted PFDS films could be degraded. Further study revealed that plasma processing of silk fabrics with PFDS would lead to the change of their chemical composition and surface roughness. As a result, the surface energy of the fabrics was reduced, accompanied by the improved water and oil repellency properties as well as enhanced antifouling performance. Besides, the plasma-grafted PFDS films also had good durability and stability. By extending the fabrics to polyester and wool against different oil-/water-based stains, the DBD plasma surface modification technique demonstrated good versatility in improving the antifouling properties of fabrics. This work provides a guidance for the surface modification of fabrics using DBD plasma to confer them with desirable functionalities.

Quick-Delivery Mold Fabricated via Stereolithography to Enhance Manufacturing Efficiency

The ever-growing demand for reducing costs and decreasing the time to market in today’s plastics industry makes rapid tooling and rapid prototyping highly researched areas. Stereolithography (SLA)-manufactured injection mold inserts make it possible to produce prototype parts rapidly and cost-effectively. To utilize SLA in the injection molding industry, two steps have to be considered. The first is to identify suitable SLA process and post-thermal curing process parameters to enhance the mechanical and thermal characteristics. The second is to verify the applicability of SLA-manufactured molds for use in the injection molding industry. IA comprehensive study was performed to find the optimum process parameters for an SLA mold with excellent mechanical and thermal properties and to verify the applicability of the mold. First of all, the mechanical and thermal properties of samples manufactured based on various laser powers and heat treatment at different temperatures were analyzed with a tensile test, DSC, and TMA according to the degree of cure. On the basis of the results from those tests, an SLA mold was designed and fabricated with the optimum mechanical and thermal properties. In addition, the SLA mold was assembled into an injection machine, and an injection molding test was conducted. The SLA mold endured during the injection cycle, and 500 shots were successfully injected without damaging the mold, which resulted in reaching the quick-delivery mold standard. Finally, we demonstrate that SLA is an effective technology to produce molds for use in the injection molding industry.

Microstructure and Mechanical Properties of Laser Powder Bed Fusion 3D-Printed Cu-10Sn Alloy

This study investigated the optimal process conditions and mechanical properties of Cu-10Sn alloys produced by the powder bed fusion (PBF) method. The optimal PBF conditions were explored by producing samples with various laser scanning speeds and laser power. It was found that under optimized conditions, samples with a density close to the theoretical density could be fabricated using PBF without any serious defects. The microstructure and mechanical properties of samples produced under optimized conditions were investigated and compared with a commercial alloy produced by the conventional method. The hardness, maximum tensile strength, and elongation of the samples were significantly higher than those of the commercially available cast alloy with the same chemical composition. Based on these results, it is expected to be possible to use the PBF technique to manufacture Cu-10Sn products with complex 3D shapes that could not be made using the conventional manufacturing method.

Development of a demulsifier and technological process study for the preparation of highly viscous heavy oils for refinement

One of the challenges in the petroleum industry is the production of highly viscous heavy oils, often accompanied by undesirable emulsion formation with very high aggregate stability. To prepare the crude oils for refinement, the oils must be destroyed. The destruction of aqueous emulsions containing highly viscous heavy oils is an intricate task owing to the comparatively small disparity in water and oil densities, as well as the high viscosity of the dispersive medium and its high content of mechanical impurities. The problem of the destruction of petroleum emulsions arises desperately during the desalination and dehydration of crude oils with a high content of emulsifiers (resins, asphalts, paraffin, etc.) The creation of a highly efficient demulsifier and the development of an optimal technological process for the preparation of highly emulsifying oils that are distinguished by the composition and quantity of emulsifiers of West Siberian oils, which are widely refined in Russia, are the ways to resolve this challenging and timely issue. This study focuses on the viscous heavy oil of the Verbliouje deposit in the Astrakhan region. It also explains the creation of an effective demulsifier for the destruction of petroleum emulsions characterized by a very high emulsifying power and the fundamental principles of the development of deep dehydration technology and desalination of such high-viscosity heavy oils.

Long-Term Optimal Scheduling of Hydro-Photovoltaic Hybrid Systems Considering Short-Term Operation Performance

Integrating photovoltaic power stations into large-capacity hydropower stations is an efficient and promising method for regulating large-scale photovoltaic power generation. However, constrained by the time step length, traditional long-term scheduling of hydro-PV hybrid systems does not adequately consider short-term operational performance indicators, resulting in sub-optimal scheduling plans that fail to coordinate the consumption of photovoltaic power and the utilization of water resources in the basin. To address this, this study established a long-term optimal scheduling model for hydro-PV hybrid systems. This model overcomes the limitation of the time step length in long-term scheduling by incorporating long-term power generation goals and short-term operation performance targets into the long-term optimal scheduling process based on scheduling auxiliary functions. In case studies, the optimised model balanced the long-term power-generation goals and short-term operational performance targets by redistributing energy across different periods. Compared to optimization models that did not consider short-term operation performance, in a typical normal year, the model effectively reduced the electricity curtailment volume (28.54%) and power shortage volume (10.91%) of the hybrid system while increasing on-grid electricity (0.03%). Similar improvements were observed in wet and dry years. These findings provide decision support for hydropower scheduling in the context of large-scale photovoltaic power integration.

Ultrasonic Welding Parameter Optimization for Electric Component Welding

Industrial requirements to establish metallic joints between dissimilar metals in the electric area. The ultrasonic welding process is an optimal process to joint thin sheets or foils. The goal of the research was to optimize the ultrasonic welding parameters to join thin nickel-coated copper sheets and aluminium sheets. It used a 0.5 mm thick high-purity copper (Cu-OF-R200) sheet coated with a 10 μm pure nickel layer and a 0.5 mm thick aluminium (1050A H24) sheet. The ultrasonic welding is made by a Branson Ultraweld L20 ultrasonic welder equipment. The mechanical properties and exacting geometrical tolerance of the joint were required. The welding parameter optimization is made empirically, with several welding tests. The optimal welding parameters were confirmed by non-destructive and destructive tests of the joints. The non-destructive tests were the visual inspection and geometrical measurements of the joint sizes. The destructive tests were tensile tests and macroscopic and microscopic tests. The completed test results confirmed the process applicability and the quality of the joint.

Taguchi optimization of Wire EDM process parameters for machining LM5 aluminium alloy.

LM5 alloy is suitable for metal castings for marine and aesthetic uses due to its admirable resistance to corrosion. In order to make intricate shapes in the LM5 alloy, this study intends to assess the impact of Wire Electric Discharge Machining process variables, like Pulse on Time (Ton), Pulse off Time (Toff), Gap Voltage (GV) and Wire Feed (WF) on responses like Material Removal Rate (MRR), Surface Roughness (SR), and Kerf Width (Kw). The LM5 aluminium alloy plate was produced through stir casting process. SEM, EDAX and XRD images confirm the LM5 Al alloy's microstructure and crystal structure. WEDM studies were conducted using design of experiments approach based on L9 orthogonal array and analysed using Taguchi's Signal to Noise Ratio (S/N) analysis. Pulse on Time has the greatest statistical effects on MRR (68.25%), SR (79.46%) and kerf (81.97%). In order to assess the surface integrity of the WEDM machined surfaces, the SEM study on the topography was conducted using the optimum surface roughness process variables: Ton 110 μs, Toff 50 μs, GV 40 V, and WF 9 m/min. SEM images show the recast layer and its thickness. The average absolute error for MRR is 1.69%, SR is 3.89% and kerf is 0.88%, based on mathematical (linear regression) models. The Taguchi's Signal to Noise ratio analysis is the most appropriate for single objective optimization of responses.

Tensile strength of friction stir additive manufactured laminated AA 6061/TiC/GS composites

Abstract With the fast progress of industrial manufacturing, friction stir additive manufacturing has fascinated wide-ranging consideration in the industry due to high material consumption rate. Friction stir additive manufacturing (FSAM), a newly developed solid-phase additive manufacturing technique was employed to fabricate AA6061/TiC/GS composite. The process parameters like tool rotational speed, transverse speed, tool tilt angle and type of tools used in friction stir additive manufacturing were analyzed. Taguchi’s L16 orthogonal array and ANOVA method was used to find the optimum process parameters for the tensile strength. Development characteristics of stirred zone, recrystallization and mixing of reinforced particles will significantly improve the mechanical properties of the fabricated composites. Microstructural investigation and fractography was done by using optical microscopy and scanning electron microscopy (SEM). Corrosion, wear behavior and elemental analysis through EDS was also performed for the fabricated material. The maximum tensile strength of 385.74 MPa was attained under optimal parameters of the tool rotational speed 1,200 rpm, transverse speed 55 mm min−1, and tool tilt angle of 1° for scrolled tapered octagonal tool pin. The findings of the linear regression model showed a minor variance between model and experimental values. Prominent results of the experiment were compared by few other researcher’s findings working in similar area.

Optimizing dry milling of stir-cast and heat-treated AZ80 magnesium alloy using multiple criteria optimization technique: an experimental study.

The primary aspects of this research are to evaluate surface roughness, cutting force, and material removal rate and optimize it with dry milling process parameters for heat-treated and stir-cast AZ80 magnesium alloy. Multiple methodologies are utilized in the research, which includes the Integration of design of experiments-response surface methodology for experimental design with the technique for order of preference by similarity to ideal solution for multi-criteria optimization. In order to evaluate the effect of process parameters on the response, the experimental design manipulates the depth of cut, feed rate, and cutting speed in a systematic manner. An evaluation of the machined surface's quality is conducted via surface roughness measurements. Likewise, insights into the forces exerted during milling can be obtained through continuous monitoring of cutting forces. The calculation of material removal rate is predicated on weight reduction. The interaction between the depth of cut and feed rate has a significant impact on the critical-to-quality characteristics of the alloy, which has contribution percentage greater than 25%. This finding validates that despite the heat-treated alloy having a similar composition to the as-cast alloy (where the closeness coefficient is 0.9843), the optimal process parameters of the former are not applicable to the latter. Nevertheless, the technique used to prepare the specimen has no bearing on the material removal rate, which is a process parameter-specific effect.

Optimization of Magnetic Field-Assisted Laser Cladding Based on Hierarchical Analysis and Gray Correlation Method

Process parameters directly affect the quality of laser cladding. In this study, magnetic field-assisted laser cladding experiments were carried out on the surface of 300 M ultra-high-strength steel by setting laser energy density, magnetic field strength, and frequency as processing parameters. The optimization of laser cladding process parameters was investigated based on evaluating the quality of the laser cladding layer through hierarchical analysis and gray correlation analysis. Based on orthogonal test data, the correlation coefficients of the process parameters with the single objective function and the correlation degree of the multi-objective function were calculated by using the gray theory. Then the comprehensive objective optimization was carried out according to the gray correlation degree. The optimization problem with multiple process objectives was transformed into a single gray correlation degree optimization method to realize the optimization of process objectives and obtain the optimal combination of process parameters. The validation experiments indicate that the quality of the laser cladding layer can be greatly improved by employing optimal process parameters. The optimized laser cladding layer shows a reduced microstructure size and enhanced wear resistance, indicating the effectiveness of the optimization approach.