Influence Of Process Parameters Research Articles

Research on Process Control of Laser-Based Direct Energy Deposition Based on Real-Time Monitoring of Molten Pool

In the process of laser-based direct energy deposition (DED-LB), the quality of the deposited layer will be affected by the process parameters and the external environment, and there are problems such as poor stability and low accuracy. A molten pool monitoring method based on coaxial vision is proposed. Firstly, the molten pool image is captured by a coaxial CCD camera, and the geometric features of the molten pool are accurately extracted by image processing techniques such as grayscale, median filtering noise reduction, and K-means clustering combined with threshold segmentation. The molten pool width is accurately extracted by the Canny operator combined with the minimum boundary rectangle method, and it is used as the feedback of weld pool control. The influence of process parameters on the molten pool was further analyzed. The results show that with an increase in laser power, the width and area of the molten pool increase monotonously, but exceeding the material limit will cause distortion. Increasing the scanning speed will reduce the size of the molten pool. By comparing the molten pool under constant power mode and width control mode, it is found that in width control mode, the melt pool width fluctuates less, and the machining accuracy is improved, validating the effectiveness of the real-time control system.

Assessment on the influence of FDM process parameters on the mechanical properties of PLA samples

Abstract The manufacturing of functional parts from the fused deposition modeling 3D printer is limited due to poor mechanical properties, low surface finish, and huge production time. During 3D printing of prototypes, the time consumption of printing and mechanical properties of the model is directly proportional. The fused deposition modeling process parameters significantly impact the quality of printed parts. The prime objective of this research is to optimize the process parameters of a 3D printing machine (wall thickness, infill percentage, infill pattern, and infill speed) using polylactic acid material to enhance the mechanical properties with less printing time of the 3D printing model. The ultimate tensile strength and elongation of the 3D printed samples are used to evaluate the mechanical properties of the various slicing process parameters as per the standards. From the results, it is evident that the mechanical properties of the 3D printed materials increased significantly. The magnitude of ultimate tensile strength is reported as 39.972 MPa with a printing time of 28 min. From close observation, it is evident that lower infill speeds with gyroid infill pattern produce the highest ultimate tensile strength of all combinations. Also, optimal results are derived at higher wall thickness and higher infill percentage. In addition to that, finite element analysis was carried out for different infill percentages of the specimen to validate the actual result.

Optimization of Laser Cladding Parameters for High-Entropy Alloy-Reinforced 316L Stainless-Steel via Grey Relational Analysis

Laser cladding technology serves as a pivotal technique in industrial production, especially in the realms of additive manufacturing, surface enhancement, coating preparation, and the repair of part surfaces. This study investigates the influence of metal powder composition and processing parameters on laser cladding coatings utilizing the Taguchi orthogonal experimental design method. To optimize the laser cladding parameters, multi-response grey relational analysis (GRA) was employed, aiming to improve both the microhardness and the overall quality of the coatings. The optimal parameter combinations identified through GRA were subsequently validated through experimental tests. The results reveal that the microhardness and quality of the coatings are substantially influenced by several critical factors, including the powder feed rate, laser power, high-entropy alloy (HEA) addition rate, scanning speed, and substrate tilt angle. Specifically, the powder feed rate exerts the most significant effect on the microhardness, dilution rate, and average contact angle. In contrast, laser power primarily impacts the mean contact angle difference. The HEA addition rate notably affects the mean contact angle difference, while the scanning speed affects the microhardness and the substrate tilt angle influences the average contact angle. The results of the validation experiment showed a deviation of only 0.95% from the predicted values, underscoring the efficacy of the grey relational analysis (GRA) in optimizing the laser cladding process parameters. The methodology presented in this paper can be applied to determine the ideal processing parameters for multi-response laser cladding processes, encompassing applications such as surface peening and surface repair.

Influence of Process Parameters on Properties of Non-Reactive RF Magnetron-Sputtered Indium Tin Oxide Thin Films Used as Electrodes for Organic Light-Emitting Diodes

Influence of Process Parameters on Properties of Non-Reactive RF Magnetron-Sputtered Indium Tin Oxide Thin Films Used as Electrodes for Organic Light-Emitting Diodes

Experimental investigations on influence of processing parameters on the microstructure and properties of AM-printed stainless steel

ABSTRACT The current study has investigated the mechanical properties and microstructure of the DMLS processed 316L experimentally by varying process parameters and solution annealing as a post-processing technique. The feedstock material characteristics, laser power input, layer thickness, scanning velocity, hatch spacing, and building direction are important factors to consider. The modified microstructure not only affects mechanical performance and corrosion resistance but also alters the specimen's properties. An analysis of the powder feedstock and density measurement has been conducted. The samples were subjected to tensile testing, hardness testing, and microstructural analysis. According to the Taguchi analysis findings, the most significant parameter affecting product quality was layer thickness. The observation of grain boundary precipitation in a few samples could be reversed through solution annealing. The results of this study will assist in determining the optimal process parameters for achieving the desired mechanical properties.

Sensitivity analysis-based quality optimization strategy for multi-correlation parameters in spinning process

To address the problem of quality optimization of multi-correlation parameters in the spinning process, this paper proposes a new method based on a sparrow search algorithm (SSA). Firstly, a generalized regression neural network (GRNN) is used to investigate the impact of the spinning process parameters on yarn quality, and quality forward modeling in the spinning process is established. And based on the coupling and correlation characteristics of spinning process parameters, sensitivity analysis is used to analyze the influence of each spinning process parameter on yarn quality, the correlation spinning process parameters for further analysis. Then a model of quality optimization with spinning process parameters is established, and SSA is used to solve the model of quality optimization with multi-correlation parameters in the spinning process. Finally, the effectiveness of the proposed method was validated through an instance. The results show that the optimal spinning process parameters combination generation of [32.159 5.2 0.8 14.8 24.540 8588.677 21.708] occurs in a configuration with a fitness value of 0.0003. The proposed sensitivity analysis-based quality optimization strategy reveals good performances in terms of both convergence speed and optimization accuracy, which will provide guidance for improving yarn quality.

Finite element simulation and experimental verification of laser machining of nitinol tubes

Nitinol tubes are widely used to cut various biological stents, especially cardiovascular stents. However, stent fabrication defects, such as residual stress, microcracks, and heat-affected zones (HAZs) from the laser cutting, can lead to severe clinical complications. In this study, a multiphase flow coupling model for fiber laser cutting simulation is established by considering surface tension, gravity, and recoil pressure and combining the characteristics of fluid heat transfer with phase transition dynamics. The accuracy of the model is verified through the fiber laser cutting experiments. The simulation model is used to explore the influence of the key process parameters of laser cutting on the kerf width, stress, temperature distribution, and the HAZ. The microscopic removal mechanism of the material during the laser cutting is revealed, thus minimizing the problems generated during stent forming. The simulation model can provide an optimized process plan for fiber laser cutting.

Optimization of defects and high temperature corrosion resistance of laser cladding FeCrAl coatings: Influence of process parameters

To enhance the surface quality and high-temperature corrosion resistance of FeCrAl coatings further, a laser cladding technique was employed to deposit Fe-13Cr-7Al coatings on the surface of 12Cr1MoV heat-resistant steel. The study investigated the influence of laser power, scanning speed, and powder feed rate on the quality and high-temperature corrosion resistance of the Fe-13Cr-7Al coatings. Utilizing 25 orthogonal experiments, coatings were prepared and evaluated through high-temperature corrosion tests to explore the corrosion resistance and mechanisms microstructural analysis of the coatings, including their elemental distribution and corrosion mechanisms, was conducted using optical microscopy (OM), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS). The optimal parameter combinations for laser cladding coatings were discussed. The results indicated that the coating quality was optimal within specific ranges of parameters (laser power 1875–2250 W, scanning speed 33–44 mm/s, powder feed rate 12–18 g/min); deviations outside these ranges led to issues such as incomplete coverage or coating detachment from the substrate. The structure of the laser cladded Fe-13Cr-7Al coatings consisted of columnar grains and α-Fe phase. In high-temperature corrosion testing, the coatings exhibited superior corrosion resistance compared to the substrate, with nearly twice the corrosion resistance variation observed under different process parameters. This study provides a scientific basis for optimizing laser cladding process parameters of Fe-13Cr-7Al coatings, demonstrating that precise control of process parameters significantly enhances the high-temperature corrosion resistance of coatings, thereby opening new possibilities for improving material performance in high-temperature applications.

Effects of scanning strategy and scanning speed on microstructures and mechanical properties of NiTi alloys by laser powder bed fusion

In this work, the influence of processing parameter including laser scanning strategy and scanning speed on grain morphology and crystalline orientation of NiTi alloys fabricated by laser powder bed fusion (L-PBF) was comprehensively investigated from the perspective of crystal growth. The results show that as the interlayer rotation angle increases from 0 to 90°, the grain morphology changes from the coarse columnar to columnar-and-equiaxed shapes, accompanied by the texture intensity first rising then reducing. Besides, increasing the scanning speed leads to a transition in grain morphology from columnar to equiaxed crystals, as well as a reduction in grain size and texture intensity. The recovery mechanism caused by different thermal histories under various scanning speeds was discussed, with a particular focus on dislocation density and its distribution. The results demonstrate that the dislocation density gradually increases with the increase of scanning speed, leaving behind more dislocations within the matrix. Furthermore, the effects of scanning speed and building direction on the compressive behavior were investigated through identifying the difference of microstructure in the NiTi alloys by L-PBF. This study highlights the relationship among processing, microstructure, and mechanical performance, paving the way for tailoring and designing microstructures and mechanical properties for the NiTi alloys by L-PBF.

Proposal of trapezoidal vibration-assisted diamond cutting for ductile-regime machining of brittle crystals: A case study on KDP crystal

Despite various vibration-assisted cutting techniques have been utilized to increase the machining performances of brittle materials, the highly dynamic variations of cutting process quantities lead to the complicated brittle-ductile transition (BDT) mechanism and the formation of undesired vibration marks on the machined surfaces. In this paper, a novel ultra-precision vibration-assisted cutting process, named trapezoidal modulation diamond cutting (TMDC), is firstly proposed for ductile-regime machining of brittle materials with significantly increased BDT cutting depth. By imposing a dedicate trapezoidal locus to the diamond tool, the unique invariable uncut chip thickness and cutting states were achieved for realizing stable vibration-assisted cutting without the formations of vibration marks. Systematic cutting experiments of KDP crystals were carried out to comprehensively investigate the influences of different process parameters on the machining performances of TMDC process. In addition, the underlying mechanisms of machining performance improvements have been discussed under the different combinations of process parameters, based on which the guidelines for optimal process parameter selection are given for increasing the BDT cutting depths. The outcomes of this study contribute to not only improving the ductile machining efficiency and machining quality of KDP crystals, but also help to deepen the understandings of BDT mechanism during vibration-assisted diamond cutting of common brittle materials.

Quantitative recovery and regeneration of basic deep eutectic solvent for biomass treatment with industrialized membrane-based strategy

As a new type of ionic liquids, basic deep eutectic solvents have been reported as emerging medium for biorefinery, extraction, catalysis and so on. Quantitative recovery with recycling of basic DES was important for the scale utilization of biomass and the environmental conservation. An electrodialysis-based method was designed for divisionally regenerating basic DES choline chloride-monoethanol amine (ChCl-MEA) after pretreatment of wheat straw. Influence of primary process parameters on recovery of ChCl-MEA was studied and recovery economy of ChCl-MEA was analyzed. Recovery ratio of ChCl and MEA varied within 89.2 %-96.0 % and 93.3 %-97.9 %. Energy consumption of ChCl-MEA recovery changed within 4.2–29.4 kW·h/kg. Transport rate of basic DES ChCl-MEA altered in the range of 12.2–464.7 mmol/(m2·min). Process economy analysis proved that recovery cost of basic DES ChCl-MEA was less than 7 % (0.81–7.07 $/kg) of DES purchase cost. Insight brought by this study indicated a technically feasible and economical approach for basic DES recycling after biomass pretreatment.

Review of Cathode Plasma Electrolysis Treatment: Progress, Applications, and Advancements in Metal Coating Preparation.

Cathodic plasma electrolytic treatment (CPET) is an emerging surface modification and coating preparation technology. By utilizing plasma discharge induced through electrolysis and the cooling impact of electrolyte, metal cleaning, saturation, and coating preparation are efficiently achieved. In this review, the principle, application, and development of the CPET process are briefly summarized based on the past literature. Detailed insights are provided into the influence of electrolyte parameters (pH, metal salt concentration, and temperature), electrical parameters (voltage, duty cycle, and frequency), and process parameters (electrode area ratio, material, roughness, and deposition time) on plasma discharge and coating formation for metal coatings. The interaction mechanism between plasma and material surfaces is also investigated. Recommendations and future research avenues are suggested to propel CPET and its practical implementations. This review is expected to provide assistance and inspiration for researchers engaged in CPET.

Additive manufacturing of wood composite parts by individual layer fabrication - influence of process parameters on product properties

Individual Layer Fabrication (ILF) is a novel additive manufacturing process that was developed to create objects with high wood content and high mechanical strength. Here, thin and individually contoured wood composite panels are created via Binder Jetting and subsequent mechanical pressing. Like in Sheet Lamination, these panels are then laminated onto each other to create a three-dimensional object. With wood contents (more than 85 mass percent) and mechanical properties (more than 30 MPa flexural strength) on par with other engineered wood products like particle boards and plywood, the produced objects are well suited for the construction and furniture industry. To gain a deeper understanding of the process, the influence of processing parameters on the geometric and mechanical properties of the finished objects were investigated. As process parameters the amounts of adhesive and the pressing forces for both panel production and lamination were selected. It was discovered that the interaction between the amount of adhesive and the pressure used to produce the panels is highly relevant for the geometric properties. The three core mechanisms that are responsible for the mechanical properties of produced parts were identified and can be ranked in the following order: 1) the amount of adhesive in the panels binding the particles, 2) the density of the panels, 3) the amount of adhesive for laminating the panels.

Removal mechanism and hole quality of SiCp/Al composites by ultrasonic elliptical vibration-assisted helical milling

SiCp/Al composites are widely used in the aerospace field due to their excellent properties. However, the huge difference in the properties of silicon carbide and aluminum matrix materials can easily lead to machining defects. Ultrasonic vibration-assisted machining is an effective method to deal with difficult-to-machine materials. In this study, ultrasonic elliptical vibration is applied to the helical milling of SiCp/Al composites. Firstly, the ultrasonic elliptical vibration-assisted helical milling (UEVHM) cutting-edge trajectory is modeled, and the equation of the UEVHM tool-chip separation condition is established, which lays a foundation for the analysis of the cutting mechanism. Then, the influence of ultrasonic elliptical vibration on the removal mechanism of SiCp/Al composites was investigated by finite element simulation. It was found that UEVHM can reduce the tearing of aluminum matrix and reduce the hole damage by changing the direction of the cutting velocity and the relative position of the cutting edge and particles. Finally, the single-factor experiment was carried out, and the surface morphology and roughness of HM and UEVHM were compared. The influence of process parameters on the surface roughness of UEVHM was analyzed. The experimental results show that compared with HM, UEVHM can reduce surface defects and exit damage, to obtain better surface roughness and exit edge quality. The increase in cutting speed can reduce the roughness, and the increase in pitch and revolution speed will increase the surface roughness.

Designing high-performance ion-exchangeable glasses with multi-objective optimization and machine learning

Ion exchange typically involves replacing smaller ions with larger ions below the glass transition temperature. This study introduces an innovative computational approach for the inverse design of ion-exchangeable glasses. It aims to simultaneously achieve high depth of layer (DOL) and surface compressive stress (CS), a task complicated by the inherent trade-offs between these properties. Traditional ion exchange experimental methods are not only time-consuming and expensive, but they also involve complex practical difficulties. Addressing these challenges, this paper introduces a novel computational approach that synergistically combines a multi-objective genetic algorithm with machine learning models. The approach involves training models on a diverse set of glass compositions to predict DOL and CS, which then guide an evolutionary algorithm to optimize these properties concurrently. Physics-informed parameters further refine the search, enabling a flexible design framework in glass manufacturing. Comprehensive experimentation and subsequent analysis affirm the proposed method's capacity to efficiently and effectively traverse the intricate design landscape of glass materials. The findings elucidated the influence of distinct compositional and process parameters on DOL and CS, facilitating the manual design process. Additionally, the study identified sixteen glass composition candidates within the SiO2–B2O3–Al2O3–MgO–Na2O system, exhibiting remarkable properties. Specifically, some compositions achieved a DOL of up to 95 μm with a corresponding CS of 890 MPa, while others attained a CS of up to 1654 MPa with a DOL of 14.72 μm.

Effect of chromic acid anodization on the corrosion resistance of laser cladding austenitic stainless steel coatings based on orthogonal tests

In this paper, Ni transition layer and Fe-based alloy coatings were prepared on HT250 by laser cladding technology, and the corrosion resistance of the coatings was further enhanced by the chromic acid anodization (CAA) surface treatment process. The effects of time (t), current intensity (I), and temperature (T) on the microstructure and corrosion resistance of the coating after CAA were explored based on the three-factor and three-level orthogonal test method. The results show that after CAA, the intergranular morphology of the coating is corroded, the intragranular organization is exposed and protrudes, and the micro-morphology shows a multi-layer "skeleton" overlapping structure. The main phases were transformed from γ-Fe (FCC) to CrNi (FCC) and FeNi (BCC). The corrosion residue of the original coating is a lamellar metal-carbide weave, whereas the CAA coating is fibrous. The order of influence of CAA process parameters on corrosion depth and maximum impedance value is I >t >T. I on the degree of densification of the passivated film is 1.03 and 1.81 times higher than T and t, respectively. The best corrosion resistance of the sample was obtained at t=30min, I=0.1A, and T=40 ℃, and its corrosion rate (2.83×10-3g/m2·h) was 29.88% lower than the original coating (4.03×10-3g/m2·h).

Numerical simulation study on solidification proceoss of titanium slab ingot by electron beam cold hearth melting

Abstract Titanium and titanium alloys are key basic support materials in the field of engineering technology and high technology, and are widely used in the fields of natural gas transportation, chemical corrosion, and marine development. Titanium alloy ingots are often prepared with more solidification defects such as surface cracks and cold shuts, resulting in lower utilization of titanium metal and higher cost of titanium products. The root of this is the lack of in-depth knowledge of the ingot melting and casting process, and the failure to control the thermal conditions of the billet in the molding process within a reasonable range. In this study, based on the Lagrange Euler algorithm, combined with ProCAST finite element software to establish a numerical model, revealing the solid-liquid interface morphology, the length of the transition region, and the change rule of thermal stress under the influence of different process parameters in the solidification process of titanium slab ingot. The results show that with the increase in pulling speed, the depth of the solid-liquid phase line and the width of the mushy zone of slab ingot increase, and the length of the transition region grows. With the increase in casting temperature, the depth of the solid-liquid phase line of the slab ingot decreases, and the mushy zone gradually becomes narrower. The casting temperature and pulling speed are positively correlated with the value of the thermal stress equivalent stress in slab ingots, and the probability of cracks in the corners and ingot surface is higher. This study provides effective theoretical guidance for the realization of stable mass production of high-quality titanium slab ingot.

3D printing of shape memory magnetorheological elastomers composites

Three-dimensional (3D) printing has been widely used to process smart composites, due to their excellent flexibility and low cost. However, it still has challenge to prepare magnetorheological elastomer (MRE) with the shape-memory properties. Here, we report a 3D direct writing (DIW) printing technology for shape-memory magnetorheological elastomer (SMRE). SMRE inks with mass fractions of 50%, 60% and 70% magnetic particles were prepared by solution blending method. Then, the SMRE was prepared by DIW technology under the magnetic field, and the influence of different process parameters on the printing quality of the material was studied. Meanwhile, the electrical conductivity, shape memory and magnetic assisted driving properties of SMRE are studied. The experimental results show that SMRE can be prepared by DIW technology and driven by temperature, electricity and magnetic fields. Magnetic field assisted programming realizes the driving of soft gripper and increases the speed of SMRE windmill by 280%.

Mesoscale Multilayer Multitrack Modeling of Melt Pool Physics in Laser Powder Bed Fusion of Lattice Metal Features

This paper reports on the development of a mesoscale multiphysics numerical model for predicting the dimensions of melt pool zones in Laser Powder Bed Fusion process, in a multilayer and multitrack application dedicated to the manufacturing of lattice metal features. In such context, a clear need emerges to study laser-matter interaction regarding the persisting questions surrounding the comprehension of melt pool. An experimental campaign involving thin pillars made of the nickel-based superalloy IN718 is presented, highlighting the complexity introduced by the thin tracks superposition. Then, a continuous mesoscale numerical model, considering heat transfer, melt pool flow, and vaporization phenomena, and its extension to multilayer-multitrack simulation is detailed. Some discussions about the numerical approach and its ability to predict the global morphology and dimensions of melt pool zones and resulting tracks after solidification are proposed. Finally, comparisons between the experiments and the numerical model show good agreement, with a maximum relative error of 8% observed for remelted zone depth. This study demonstrates the capability of the present approach to help in understanding the influence of process parameters on melt pool shape and, thereafter, to determine process parameters to optimize for lattice features building.

Autothermal downdraft oxy-steam co-gasification of biomass and plastic wastes for hydrogen-rich syngas production: An Aspen plus modelling

The potential of H2-rich syngas generation using downdraft co-gasification of biomass and plastic wastes is investigated using an autothermal restricted equilibrium study using Aspen Plus. A comprehensive sensitivity analysis is carried out to impart the influence of important process parameters, viz. equivalence ratio(ER: 0.1–0.5), feed plastic content(FPC: 0–30 %), steam to feed ratio(SFR: 0–4) and steam temperature(150–1000 °C) on performance parameters, viz. syngas composition, gasification temperature(GT), lower heating value(LHV), cold gas efficiency(CGE), gasification energy efficiency(GEE) and hydrogen energy efficiency(HEE). The ER and SFR showed dominant effects on performance. The increase in ER from 0.1 to 0.5 causes an increase in GT from 565 °C to 1734 °C. The highest syngas H2 content and HEE of 52.1 % and 36.9 %, respectively, are obtained for 0.25 ER. The increase in SFR improves the syngas H2 content at the cost of LHV and GEE, with the highest HEE of 36.9 % obtained at 0.25 ER. The analysis of variance(ANOVA) and response surface methodology(RSM) has also been studied along with the multi-objective optimisation(MOO).