Process Parameter Window Research Articles

Process simulation and optimization of process parameters of single-pulse femtosecond laser processing Invar 36 alloy

Invar 36 alloy has an extremely low coefficient of thermal expansion and is suitable for preparing a fine metal mask (FMM) for the evaporation of silicon-based organic light emitting display microdisplays. The higher the resolution and the greater the number of pixels, the finer and more delicate the holes required. Femtosecond laser processing technology is an effective technical means for processing Invar 36 alloy FMM due to its characteristics of extremely short pulse width, extremely high pulse energy density, smaller heat-affected zone, and more regular machining edges. The femtosecond laser processing parameters directly affect temperature distribution and then affect the manufacturing quality and efficiency of Invar 36 alloy FMM. At present, femtosecond laser processing of Invar 36 alloy FMM is still in the exploration stage, and the processing mechanism and technology are not clear. In this paper, a simulation model of single-pulse femtosecond laser processing Invar 36 alloy is established based on the two-temperature equation. By comparing the ablation morphology of the simulation output with the experimental measurement results, the validity of the simulation model is verified and the processing mechanism is preliminarily explored. Based on the simulation model, the effects of femtosecond laser energy density, pulse duration, and spot diameter on the electron temperature field, lattice temperature field, and ablation morphology of the craters are explored. The process window of laser processing parameters is determined. A full-factor test is conducted. Take the minimum length of the heat-affected zone, the maximum depth of the ablation crater, and the minimum diameter of the ablation crater as three optimization objectives and obtain Pareto optimal solutions based on genetic algorithm. The optimization of single-pulse femtosecond laser drilling Invar 36 alloy is realized.

Optimizing the diamond wire sawing of polycrystalline silicon: An experimental approach

This study aims to determine the optimized cutting conditions for diamond wire sawing of polycrystalline silicon (poly-Si) wafers using a laboratory machine-tool that employs continuous cutting movement and reach cutting conditions similar to those in the industry. The experimental cutting was carried out following a central composite design, varying the wire cutting speed (vc) and feed rate (vf). A response surface methodology was employed to find the optimized cutting conditions for minimum surface roughness and subsurface micro-crack depth of the as-sawn poly-Si wafer. The results showed that the as-sawn poly-Si exhibited ductile scratches and fragile fractures in its surface morphology, with high vc and low vf resulting in a smooth surface. The response surfaces indicated that increasing vf led to increased Ra and Rq values, while increasing vc reduced them. Median micro-cracks were slightly inclined in the subsurface region, with the response surface indicating that their depth reduced with increasing vc and decreasing vf. The vf/vc ratio significantly affected surface integrity, with a lower vf/vc ratio being more suitable for reaching a smoother surface and shallower subsurface damage. The following material removal mechanisms was identified: optimal ductile region, ductile-to-brittle transition, brittle-ductile mixture region, and brittle region. Simulations using the response surface models indicated minimum values of Ra = 0.35 μm, Rq = 0.48 μm and SSD = 3.29 μm. Thus, this study provides a processing parameter window for diamond wire sawing of poly-Si wafers, which could be useful for both the photovoltaic and microelectronic industries.

Investigating the process parameter window for laser powder bed fusion of copper chrome zirconium

ABSTRACT Copper-based alloy UNS C18150 has become an attractive material for laser powder bed fusion (LPBF) processing. However, the complexity of LPBF mandates that unique process parameters be devised for each alloy as these are highly sensitive to material chemistry. This work aims to clarify the general boundaries of the process window for the most influential parameters alongside an exploration into the effects of scan strategy on the density. A series of statistical design of experiments were utilised to model density as a response and predict process parameters that would result in minimised residual porosity. Using optimised parameters, specimen with up to 99.1% of theoretical density were produced, and a window of process parameters was established that yielded similarly dense products. Post-build aging of the LPBF parts was also explored. Here, direct aging of the as-built product at 390°C for 100 h resulted in a peak hardness of 83.3 ± 0.6 HRB.

Optimization design and interface characteristics research of high damping NiTi - Nickel-Aluminum Bronze functional gradient composite coating additively manufactured by high-speed laser-directed energy deposition

The near-equatomic NiTi shape memory alloy demonstrates exceptional damping performance due to its distinctive low-temperature self-cooperative martensitic internal friction. This study successfully fabricated NiTi-NAB (Nickel-Aluminium bronze shape memory alloy) functionally graded composite coatings with excellent metallurgical bonding between layers on Q235 steel substrates by designing an appropriate interlayer structure and employing the high-speed laser-directed energy deposition (LDED). Through comprehensive evaluation of the composite coating's performance and the numerical simulations of heat transfer within the molten pool, we elucidated the impact of process parameter levels on the microstructure and phase transformation characteristics of the NiTi alloy coating (NTC). The phase composition and phase interface characteristics of the NTC surface and bonding interface were analyzed using an electron probe microanalyzer and transmission electron microscopy, while dynamic thermomechanical analysis was employed to evaluate the damping performance of the NTC. The results indicate that an optimal parameter combination area still exists within the NTC-LDED process parameter window, even with equal laser energy density. Insufficient parameter levels can lead to an increase of micro-defects within the NTC, consequently causing a deterioration in both the cohesion and deformation resistance of the coating. Excessively high parameter levels can lead to significant element loss and residual stress, which in turn contributes to an increase in microcracks within the coating. A considerable quantity of reaction product mixture phases was formed at the interface between NTC and NAB, tending to align coherently with the NAB phase interface. The NTC, prepared with optimal process parameters, exhibits exceptional damping performance with a damping ratio of 0.498 at internal friction equilibrium, rendering it highly promising for applications in surface erosion protection for fluid machinery.

Development of parametric window and optimization of process parameters to predict bead profile in magnetically controlled gas tungsten arc welding

A novel methodology has been proposed to tame the arc shape by adopting an external magnetic field, resulting weld profile as required. The co-axial magnetic field developed by specially designed electromagnets is superimposed on the welding arc. It was found that 0-0-S-N configuration provided more penetration than conventional gas tungsten arc welding. A parametric window has been developed for the selected configuration to obtain the desired bead geometry. The experiments were performed using process parameters as suggested by the design matrix, developed using response surface method technique. Mathematical models were evolved from experimental data for penetration and bead width. The evolved model for penetration is adequate up to 99.72% confidence level and for bead width is 99.98% confidence level. The effects of process parameters have been presented in a graphical manner for better understanding. The penetration achieved with the magnetically controlled GTAW process is 3.92 mm, which is 30% more than that achieved with conventional GTAW. The bead width increases initially, up to a certain limit, and then reduces with an increase in excitation current. Further, the experiments have been conducted on the optimized parameters for the validation of models. The refined grains were obtained due to magnetic stirring of the molten pool, which is desirable for improvement in mechanical properties of welds. The average grain size was reduced from 42.55 to 31.03 µm. The improved microstructure containing more amount of acicular ferrite was obtained with magnetically controlled arc.

Data-Physics Fusion-Driven Defect Predictions for Titanium Alloy Casing Using Neural Network.

The quality of Ti alloy casing is crucial for the safe and stable operation of aero engines. However, the fluctuation of key process parameters during the investment casting process of titanium alloy casings has a significant influence on the volume and number of porosity defects, and this influence cannot be effectively suppressed at present. Therefore, this paper proposes a strategy to control the influence of process parameters on shrinkage volume and number. This study constructed multiple regression prediction models and neural network prediction models of porosity volume and number for a ZTC4 casing by simulating the gravity investment casting process. The results show that the multiple regression prediction model and neural network prediction model of shrinkage cavity total volume have an accuracy of over 99%. The accuracy of the neural network prediction model is higher than that of the multiple regression model, and the neural network model realizes the accurate prediction of shrinkage defect volume and defect number through pouring temperature, pouring time, and mold shell temperature. The sensitivity degree of casing defects to key process parameters, from high to low, is as follows: pouring temperature, pouring time, and mold temperature. Further optimizing the key process parameter window reduces the influence of process parameter fluctuation on the volume and number of porosity defects in casing castings. This study provides a reference for actual production control process parameters to reduce shrinkage cavity and loose defects.

Dependences of the defect, microstructure and properties of 15-5 PH martensitic stainless steel on the laser powder bed fusion process parameters

15-5 PH martensitic stainless steel is widely utilized in the marine, chemical, and aerospace industries owing to its high strength and corrosion resistance properties. The highly tailored samples can be produced via laser powder bed fusion technology, however it is still unknown how to optimize process parameter windows and conduct mechanism research for 15-5 PH steel forming. The results show that fusion defects are mostly concentrated in the region with low laser power (P) of 200 W, and there is no obvious distribution pattern in the pore and porosity defects. Excellent dense samples can be formed mainly at medium P of 260 W and medium scanning speed (V) of 1200 mm/s. The proportion of body center cubic structure reaches 91.7 % for the hatch space (H) of 0.06 mm, and a heterogeneous layered structure with alternating fine and coarse grain layers is formed. The sample exhibits high strength and excellent plasticity, where the ultimate tensile strength, yield strength, elongation to fracture, impact toughness, and hardness are 1161 MPa, 825 MPa, 17.5 %, 122.5 J/cm2, and 34.6 HRC, respectively. The excellent comprehensive property is due to fine-grained strengthening, dislocation strengthening, solid solution strengthening and intrinsic factors/oxide dispersion strengthening.

Optimization and GRA prediction of Al–Cu pulsed laser welding process based on RSM

In this paper, the process parameters of pulsed laser welding of Al–Cu are studied using response surface methodology (RSM) and grey relation analysis (GRA) to propose optimal directions for lap-shear strength of the joints. A single-factor experiment was conducted to find the suitable process parameter windows. The RSM models were established and analyzed with laser power, welding speed, pulse width, and frequency as inputs and joint lap shear, interfacial weld width, and weld-penetration-depth as outputs. With the use of GRA of interfacial weld width and weld penetration depth with the lap-shear force of joints, the improved direction for the lap-shear force of joints can be proposed.

Research on the Process of Laser Cladding Ni60 Coating on High-Nickel Cast Iron Surfaces

In order to achieve high-performance coatings on the surface of electric submersible pump impellers, it is crucial to optimize the laser cladding process parameters. Using Ansys 2021 R1 commercial software, a numerical simulation of laser cladding Ni60 powder on high nickel cast iron was conducted. The simulation utilized a 3D Gaussian heat source, parametric language, and life–death unit technology to replicate the characteristics of synchronous powder delivery laser cladding. The study focused on analyzing the temperature field cloud map and molten pool size under different laser power and scanning speeds, narrowing down the process parameter window, selecting optimized laser power and scanning speed, and assessing the changes in surface morphology, melting height and width, dilution rate, microhardness, and microstructure of the laser cladding coating. Results indicate that the coating width and thickness increase with higher laser power and lower scanning speeds. The microstructure consists primarily of dendritic, block, short rod, and long strip formations, and exhibits a tightly distributed and uniform grain structure. Furthermore, the microhardness of the coating shows a negative correlation with laser power and scanning speed. The optimal process parameters were determined to be a laser power of 1100 W and a scanning speed of 6 mm/s. A comparison with the simulation confirmed the effectiveness of the simulation in effectively guiding actual production.

Feasibility of Melting NbC Using Electron Beam Powder Bed Fusion

High melting point materials such as ceramics and metal carbides are in general difficult to manufacture due to their physical properties, which imposes the need for new manufacturing methods where electron beam powder bed fusion (EB‐PBF) seems promising. Most materials that have been successfully printed with EB‐PBF are metals and metal alloys with good electrical conductivity, whereas dielectric materials such as ceramics are generally difficult to print. Catastrophic problems such as smoking and spattering can occur during the EB‐PBF processing owing to inappropriate physical properties such as lack of electrical, and thermal conductivity and high melting point, which are challenging to overcome by process optimization. Due to these difficulties, a limited level of understanding has been achieved regarding melting ceramics and refractory alloys. Herein, three different substrates of niobium carbide (NbC) are melted using EB‐PBF. The established process parameter window shows a good correlation between EB‐PBF process parameters, surface, and melt characteristics, which can be used as a baseline for a printing process. Melting NbC is proven feasible using EB‐PBF; the work also points out challenges related to arc trips and spattering, as well as future investigations necessary to create a stable printing process.

Modeling and numerical studies of high-precision laser powder bed fusion

In order to comprehensively reveal the evolutionary dynamics of the molten pool and the state of motion of the fluid during the high-precision laser powder bed fusion (HP-LPBF) process, this study aims to deeply investigate the specific manifestations of the multiphase flow, solidification phenomena, and heat transfer during the process by means of numerical simulation methods. Numerical simulation models of SS316L single-layer HP-LPBF formation with single and double tracks were constructed using the discrete element method and the computational fluid dynamics method. The effects of various factors such as Marangoni convection, surface tension, vapor recoil, gravity, thermal convection, thermal radiation, and evaporative heat dissipation on the heat and mass transfer in the molten pool have been paid attention to during the model construction process. The results show that the molten pool exhibits a “comet” shape, in which the temperature gradient at the front end of the pool is significantly larger than that at the tail end, with the highest temperature gradient up to 1.69 × 108 K/s. It is also found that the depth of the second track is larger than that of the first one, and the process parameter window has been determined preliminarily. In addition, the application of HP-LPBF technology helps to reduce the surface roughness and minimize the forming size.

Evaluation of direct ink write processing parameter window via machine learning

Direct ink writing 3D printing offers significant advantages for fabricating soft materials. It is a process of forming solid parts from extruded line structures, so the uniformity and stability of the line is critical for successful printing. This study mainly focuses on the process parameter window for achieving uniform and stable printed lines. Four machine learning models (support vector machine, backpropagation neural network, decision tree, and K-nearest neighbour) are built to predict the success of printing. These models exhibited robust predictive capabilities, particularly the backpropagation neural network and support vector machine models, both achieving an accuracy of 0.9091. Utilizing these models, the reasonable processing parameter window and the relationships among printing parameters were analysed. The results indicate that high printing speeds require large extrusion pressure to achieve a high success rate. An increase in nondimensional nozzle height enhances the possibility of successful printing with small pressure and low speed. The predicted processing parameters derived from the machine learning model were applied to print representative structures, showing good prediction performance.

Fast spatial laser beam modulation for improved process control in Laser Powder Bed Fusion

We report on the implementation of a high frequency beam oscillation (wobbling) strategy for improving process control during laser powder bed fusion of single weld tracks on Inconel 625. Oscillation frequencies ranging from ~ 600 Hz to 7000 Hz, and different oscillation trajectories (circular, parallel or perpendicular to the direction of scanning) were explored. Highspeed imaging was used to elucidate the dynamics of the melt pool induced by the wobble beams, along with in situ absorptivity measurements to substantiate our hypothesis that the dynamic nature of wobble beams reduces absorptive losses due to laser-vapor interactions and results in improved coupling at the melt pool. Operando X-ray radiography was carried out to visualize sub-surface melt flow dynamics, correlate to spatter mechanisms and optimize the window for improving process stability. Our observations indicate that wobble beams increase the aspect ratio of the melt pool by up to 4×, depending on the oscillation frequency and energy input. Highspeed imaging and X-ray radiography reveal an optimized process parameter window for reducing spatter, improving absorptivity and creating a stable melt pool at high (several kHz) oscillation frequencies.

A novel laser continuous powder bed fusion of TA15 titanium alloy: Microstructure and properties

This work presents a novel laser continuous powder bed fusion (L-CPBF) process technique, tailored for the additive manufacturing of intricate components with annular hollow structures, emphasizing both precision and efficiency. Utilizing this advanced L-CPBF method, Ti-6.5Al-2Zr-Mo-V (TA15) titanium alloy samples were successfully fabricated, and their microstructures and properties were investigated. The optimized process parameter window for L-CPBF processing of TA15 was determined through Taguchi experiments, ranging from 100 to 125 J/mm3, with the relative density of the samples achieved an outstanding 99.95%. Microstructural evolution under varying volumetric energy densities (VED) was revealed through characterization methods such as SEM and EBSD. The formation of acicular α′-martensites was observed during initial the cooling phase, with thermal cycling temperature playing a pivotal role in the development of martensites of varying sizes. Furthermore, through process optimization, remarkable mechanical properties, with a tensile strength of 1200.5 ± 98.5 MPa, a yield strength of 1109 ± 102 MPa, and an elongation of 7.05 ± 1.35% were achieved. These mechanical properties are comparable to those of TA15 alloys prepared by traditional reciprocating scraper powder spreading L-PBF. However, our approach boasts a substantial increase in manufacturing efficiency, surpassing the traditional method by over 45%. Collectively, this study offers invaluable theoretical and experimental insights, paving the way for accelerated additive manufacturing of hollow annular components in demanding sectors such as aerospace and beyond.

Characterization and process optimization of remote laser cutting of current collectors for battery electrode production

Aluminum (Al) and copper (Cu) metal foils of thickness 6–20 µm are employed as current collectors for the production of Li-ion battery cathodes and anodes. Greater demand for this product is driving up production rate requirements, especially in the field of car manufacturing. Laser-based cutting processes for trimming and cutting electrodes are considered suitable for meeting this demand as they can achieve very high throughput while maintaining process quality. In order to meet market requirements, laser manufacturers are developing new laser sources, optics, and scanning heads that will improve process productivity and quality. Establishing the relationship between the laser system and cut quality will lead to competitiveness, increased productivity, and sustainability production. This paper presents a thorough analysis of the cutting performance of pulsed and continuous-wave lasers with scanning speeds of up to 28 m/s for processing thin Al and Cu current collectors. Comparisons between process outcomes are made in terms of maximum and minimum cutting speed and power, kerf geometry, cut quality, and presence of defects. Identification of configurations leading to high and low cut quality enables detailed process parameter windows to be defined for both laser system systems employing continuous-wave and pulsed sources. By analyzing correlations between the materials, laser source, and process variables, the main outcome is that continuous-wave single-mode fiber lasers enable highest cut quality in the high-productivity regime, surpassing the current state-of-the-art in laser cutting of metal foils.

Process advantages of laser hybrid welding compared to conventional arc-based welding processes for joining thick steel structures of wind tower

The most common welding processes when joining thick-walled steels in the industry are arc-based welding processes such as GMAW or SAW. For this purpose, the sheets are joined in multi-layer technique, which can lead to productivity losses due to high welding times. The process-specific challenges in welding thick steels using multi-layer technique relate to the high heat input from the process. Therefore, alternative welding processes are being actively sought. A suitable alternative is provided by beam-based welding processes such as the laser hybrid welding processes, which are characterized by deep penetration welds and lower heat input. With implementation of the laser hybrid welding process in the heavy industry, such as the wind tower industry, economic benefits can be reached such as the increase in productivity by reducing the layer number, and the lower consumption of filler material and energy. When comparing SAW welded 25 mm thick steels in five to six layers and single-pass laser hybrid welding, the welding time can be reduced more than 80 % and the costs of filler material, flux and energy can be saved up to 90 %. However, the industrial use of the laser hybrid welding process is still limited to applications, where the material thickness does not exceed 15 mm due to some process-specific challenges such as the sagging, sensitivity to manufacturing tolerances such as gaps and misalignment, limited filler wire mixing, and deteriorated mechanical properties resulting from high cooling rates. To overcome these challenges, a contactless electromagnetic backing based on an externally applied AC magnetic field was used. Eddy currents are induced due to the oscillating magnetic field, and an upward-oriented Lorentz force is generated to counteract the droplets formed due to gravitational forces. It allows to weld up to 30 mm thick structural steels in a single-pass with a 20-kW fiber laser system. Additionally, the gap bridgeability and the misalignment of edges were increased to 2 mm when welding 20 mm thick steels. With the aid of the AC magnetic field, a vortex was formed in the weld root, which had a positive effect on the filler wire mixing. A further significant advantage of the EM backing was the possibility to expand the process parameter window to maintain desired cooling times and mechanical properties, without suffering adverse effects concerning the root quality of the weld.

A multi-objective optimization of laser cladding processing parameters of AlCoCrFeNi2.1 eutectic high-entropy alloy coating

In order to obtain the optimal processing parameters for laser cladding (LC) of AlCoCrFeNi2.1 eutectic high-entropy alloy, a multi-objective optimization method based on response surface methodology (RSM) was proposed. In this paper, a one-way pre-test was conducted by varying the processing parameters using a single control variable method. The results show that the porosity and microhardness of the coating are closely related to the processing parameters. The cross-section microhardness of the coating showed instability under certain process parameters, based on which the optimization window of RSM processing parameters was determined. In the RSM model, a mathematical prediction model was developed according to the laser power, scanning speed, powder feeding rate and microhardness, dilution rate and aspect ratio. Microhardness is inversely correlated with laser power and positively correlated with scanning speed and powder feeding rate. The optimal processing parameters (laser power: 1675 W, scanning speed: 7.8 mm/s and powder feeding rateing rate: 12.91 g/min) were determined. The model showed a good agreement with the experimental validation results. The coatings have good shape with an average microhardness of 322 HV0.2. The maximum average error between model predictions and experimental validation was 5.27 %.

Prediction of melt pool geometry by fusing experimental and simulation data

Accurate prediction of the melt pool geometry in laser-directed energy deposition (L-DED) is crucial for ensuring product quality. Although machine learning methods have offered aid in addressing this challenge, existing surrogate models are typically based on either simulation or experimental data. Surrogates trained using numerical simulation data reflect modeling assumptions in their accuracy. Conversely, surrogates developed using experimental data would demand a substantial investment of effort and resources to generate adequate data for training. As a possible solution, in this paper, a multi-fidelity Gaussian process (MFGP) framework is developed to fuse experimental and simulation data. Experimental melt pool dimensions are obtained from single-layer, single-track deposits fabricated via powder-fed L-DED. These constitute the high-fidelity/ground truth data for the MFGP surrogate. An analytical Eagar-Tsai model is calibrated and queried at sampled input points within a predefined process parameter window to yield near-accurate estimates of low-fidelity melt pool data at a significantly lower effort. Thereafter, the MFGP surrogate is designed on the combined sources of data using an appropriate kernel and adequate calibration. An elaborate assessment of the trained surrogate on unseen experimental data is shown to yield results with high accuracy and low uncertainty. The proposed method of blending experimental data with simulation data has the potential to reduce the volume of experimental data required for creating surrogates without compromising accuracy. While the current work focuses on the L-DED of a popular alloy, SS316L, it can be easily extended to other advanced manufacturing processes to design reliable surrogates.

Predicting temperature field in keyhole-mode selective laser melting with combined heat sources: a rapid model

Predicting the temperature field during selective laser melting (SLM) is crucial for improving the performance of printed parts. However, there is still a lack of an efficient and accurate model for predicting the temperature field of keyhole-mode melting in SLM. Based on the physical phenomena of keyhole-mode melting observed in experiments and simulations, this study proposes an analytical model for rapidly predicting the temperature distribution during SLM keyhole-mode melting. The model considers vapor depression in the molten pool and the interaction between the laser and molten pool during keyhole-mode melting. The model was validated using numerical simulations and experimental data. The variation trend of the laser energy distribution and molten pool size with respect to the laser energy density was revealed. As the laser energy density increased, the depth of the molten pool and the vapor depression increased linearly, and the molten pool width increased to a peak and then remained constant. The process parameter window to avoid a lack-of-fusion was also investigated. With a computation time of 15 s and a prediction error of less than 10%, this model is an effective way to simulate SLM processes and guide the optimization of process parameters.

Effect of powder particle size distribution and contouring on build quality in electron beam powder bed fusion of a medium-C hot-work tool steel

An electron beam powder bed fusion (EPBF) printability study of a medium-C hot-work tool steel with focus on part density and surface roughness was performed using three different powder particle size distributions (PSDs) of 45–105 mathrm{mu m} (typical for EPBF), 20–60 mathrm{mu m} (typical for laser beam powder bed fusion), and a 50–50 wt.% mixture of these two powders. First, acceptable process parameter windows were generated based on as-printed density for each PSD. Full density parts (at least 99.5% dense according to NIST) were produced using the 20–60 mathrm{mu m} PSD and the mix PSD. Fifteen different contouring strategies were also tested for potential improvement of the as-printed side surface roughnesses, which ranged from 23.3 to 25.7 mathrm{mu m} among the three PSDs. Side surface roughness as low as 13.8 mathrm{mu m} was attained by using contouring strategies employing two contouring lines, which were typically observed to be more effective than one-line strategies. Overall, the 20–60 mathrm{mu m} PSD was determined to convey a better as-printed build quality over a wider range of parameters without sacrificing process productivity.