Laser Welding Process Parameters Research Articles

The Impact of Welding Parameters on the Welding Strength of High Borosilicate Glass and Aluminum Alloy

This study adopts a new surface pretreatment method, Laser Surface Remelting (LSR). This experiment aims to establish a set of laser welding process parameters suitable for aluminum alloy and glass under this specific pretreatment. This experiment explores the impact of laser welding parameters on the welding strength between high borosilicate glass and aluminum alloy. The study specifically investigates the effects of four process parameters: defocus amount, laser power, frequency, and pulse width on the welding outcome. The results indicate that the welding quality between the aluminum alloy and glass reaches its optimum when the defocus amount is zero (i.e., when the laser converges at the interface between the glass and the metal) and the laser welding parameters are set to a power of 250 W, a welding speed of 1 mm/s, a welding frequency of 10 Hz, and a pulse width of 2.5 ms. The experiment also analyzes the fracture morphology under different parameters, summarizing the locations and causes of fractures, and establishing the relationship between the fracture location and the welding strength.

Effect of laser welding parameters on the microstructure and tensile properties of low-alloy high-strength steel

Abstract The studying employed orthogonal experimental approach to optimize the laser welding process parameters for HC420LA low-alloy high-strength steel. Through metallographic analysis, microhardness testing, and tensile testing, the study assessed and contrasted the properties of laser-welded and arc-welded joints. The findings revealed that the most optimal laser welding conditions were 1.8 kW laser power, 2.5 m min−1 welding speed, and a focus distance of 1.5 mm, resulting in a well-formed ‘X’ shaped weld bead. Comparative analysis demonstrated that the laser-welded joint exhibited a finer microstructure, primarily composed of bainite and ferrite, whereas the arc-welded joint consisted of ferrite and martensite. Notably, the laser-welded joint exhibited superior mechanical properties, including increased microhardness and tensile strength, underscoring the distinct advantage of laser welding technology in high-strength steel welding, particularly in enhancing the weld joint’s quality and performance.

Gap bridging in laser welding of EN AW 5083 with different joint configurations via beam oscillation and filler wire

The extended use of laser welding in the industry requires a less sensitive process in terms of geometrical tolerances of the joint edges. As the industrial availability of laser systems increases, the demand to use laser welding technology possibly with parts coming from less precise production steps is increasing. Gap formation is often caused by the edge quality of the parts coming from previous manufacturing steps such as sheet forming. Al alloy sheets deformed to box-shaped 3D forms often require welded joints on the edges in lap, but, and corner joint configurations. These joints are hard to carry out by laser welding due to the large gap formation caused by the tolerances of the deformation processes involved. Laser welding of Al alloys is already challenging in the absence of gap formation, while these joint configurations have been not feasible with a stationary beam due to incomplete fusion and defect formation. Laser welding with beam oscillation and wire feeding can improve the weldability of these joints. The oscillating motion of the high-intensity beam can achieve a deep weld together with a wider seam. Combined with wire feeding, the process can close gaps in the butt, lap, and corner joint configurations. On the other hand, the added oscillation and wire-related parameters require extending the experimental space, which requires a methodological study to identify feasible conditions. Accordingly, this work proposes a methodological approach to identify and set laser welding process parameters with beam oscillation and wire feeding for an EN AW 5083. Process parameters were initially studied using a simple analytical model that depicts the beam trajectory. Bead-on-plate tests were conducted to assess beam size, power, and weld speed ranges. Lap, butt, and corner joint conditions with a 0.5-mm gap were welded with high quality by manipulating the laser power, oscillation amplitude, and wire feed rate. The results show that welding speeds could be maintained as high as 55 mm/s with complete filling of gaps of up to 0.5 mm, eliminating the surface undercuts and achieving weld widths in the order of 2.5 mm. Moreover the results show the possibility control the depth of the welds from 3 mm to full-penetration conditions.

Interpretable multi-task neural network modeling and particle swarm optimization of process parameters in laser welding

The process parameters directly affect the quality and performance of laser welding (LW) by shaping the molten pool appearance. However, with the increase in the dimensions of process parameters and the number of samples, the relationship between process parameters and molten pool often exhibits high levels of uncertainty and nonlinearity. Machine learning (ML) techniques have been used for complex LW systems modeling, but they may be limited and unable to fully capture the complex relationships when faced with complex systems. Additionally, traditional ML techniques may lack interpretability within the model, making it difficult to understand the input features and their impact on the output. To address these issues, a method that combines an interpretable multi-task neural network (MTNN) and particle swarm optimization (PSO) is proposed. Firstly, an LW experimental platform is constructed, and the orthogonal design is conducted for data collection. In the data preparation stage, the curriculum learning strategy is employed to reorganize the raw experimental data. Subsequently, the MTNN is constructed to automatically learn feature representations among input process parameters, capture nonlinear relationships between data, and share weights across multiple related tasks to improve efficiency and performance. Furthermore, the PSO is designed to determine the constraints and objective functions. In addition, the shapley additive explanation (SHAP) method is utilized to calculate the importance of process parameters and enhance the interpretability. Finally, the optimization results are validated, and the results demonstrate that the optimized results of the proposed method have achieved satisfactory performance compared to the traditional ML methods.

Microstructural Characteristics and Properties of Laser-Welded Diamond Saw Blade with 30CrMo Steel.

In order to enhance the quality of diamond composite materials, this work employs a Cu-Co-Fe and Ni-Cr-Cu pre-alloyed powder mixture as a transition layer, and utilizes laser-welding technology for saw blade fabrication. By adjusting the laser-welding process parameters, including welding speed and welding power, well-formed welded joints were achieved, and the microstructure and mechanical properties of the welded joints were investigated. The results demonstrate that the best welding performance was achieved at a laser power of 1600 W and a welding speed of 1400 mm/min, with a remarkable tooth engagement strength of up to 819 MPa. The fusion zone can be divided into rich Cu phase and rich Fe phase regions, characterized by coarse grains without apparent preferred orientation. The microstructure of the heat-affected zone primarily consists of high-hardness brittle quenched needle-like martensite, exhibiting a sharp increase in microhardness up to 550 HV. Fracture occurred at the boundary between the fusion zone and the heat-affected zone of the base material, where stress concentration was observed. By adjusting the welding parameters and transition layer materials, the mechanical properties of the joints were improved, thereby achieving a reliable connection between diamond composite materials and the metal substrate.

Multiobjective optimization of laser welding parameters for P92 steel based on MFO/MOEAD-Kriging

P92 steel is used in steam equipment of thermal power plants and nuclear power plants. It needs to withstand high temperature and high pressure during service, so high-quality welds are required. Laser welding can easily obtain good weld quality and reduce the probability of coarse grains and welding defects in the heat-affected zone. Post-weld deformation, residual stress, and weld hardness are important indexes for evaluating weld quality, which largely depends on the combination of laser welding process parameters. The multiobjective optimization methods of moth-flame optimization (MFO) and multiobjective evolutionary algorithm based on decomposition under the Kriging model were compared in this research. It was found that the MFO algorithm has a faster optimization speed and better overall effect. The Optimal Latin hypercube sampling method was used to design the simulation test. The welding seam-forming process was simulated by the SYSWELD software. The Kriging model was used to make the nonlinear relationship between the process parameters and the weld quality indexes significant. A new data set was designed to evaluate the accuracy of the model. On this basis, the efficiency of the combination of process parameters optimized by the two algorithms was compared. The simulation and experimental results were in good agreement with the multiobjective optimization results of the MFO. In the experimental verification, the optimized weld quality was analyzed from the aspects of microstructure and mechanical properties. The results showed that the multiobjective optimization method quickly and effectively reduces the probability of weld quality defects in actual welding, thereby improving weld quality. This multiobjective optimization method provides valuable research ideas for engineering research and development to effectively shorten its development cycle.

Laser Beam Welding Parametric Optimization for AZ31B and 6061-T6 Alloys: Residual Stress and Temperature Analysis Using a CCD, GA and ANN

Laser beam welding (LBW) is a technology that efficiently joins materials using a concentrated laser beam, providing advantages such as a small heat-affected zone (HAZ), high precision, adaptability to various materials, and seamless integration into automated processes. Precision in LBW is limited by challenges in selecting appropriate process parameters, performing expensive and risky physical experiments, and dealing with materials with high thermal conductivity and low melting temperatures, such as AZ31B and AA6061. This study aims to predict laser welding process parameters, encompassing beam power (4000W-6000W), spot size (0.4mm-0.8mm), welding speed (30mm/s-50mm/s), and segment number (5-15) utilizing the Response Surface Methodology (RSM), Genetic Algorithm (GA) and backpropagation neural networks. Beam power significantly affects peak temperature, leading to deeper laser penetration and a higher maximum temperature, while the segment number plays a crucial role in residual stress by potentially causing uneven cooling and distinct thermal gradients. The ANN results confirm the model's accuracy and the GA-predicted process parameters include a laser power of 4000W, welding speed of 50mm/s, spot size of 0.6mm, segment number of 15, peak temperature range of 888.9°C to 1020.5°C, and a preferred equivalent stress of 1396.62 MPa.

Multi-objective optimization of laser welding process parameters of steel/Al based on BO-RF and MOJS

Multi-objective optimization of laser welding process parameters of steel/Al based on BO-RF and MOJS

Optimization of laser welded ASTM A36 mild steel with different laser beam oscillation patterns utilizing experimental and simulation data

Recently, there has been an increase in the use of laser beam welding of mild steel in various industries, including petroleum refineries, power plants, pharmaceuticals, and even residential areas. This research paper focuses on studying the effects of laser welding process parameters, such as laser power and welding speed, on the tensile strength of welds. To do this, three types of laser beam oscillations (sinusoidal path, triangular path, and square path) were performed to weld 125mm x 60 and 1.8 thick sheets of ASTM A36 mild steel alloy. The researchers used statistical tools such as ANOVA to generate mathematical models and experimental designs using the Taguchi method. The results indicate that the optimal welded joint has good mechanical properties after laser welding. For ASTM A36 mild steel, the optimal parameters for laser welding are a laser power of 1800 W, a welding speed of 50 mm/s, and triangular welding mode.

Laser welding of GH3539 alloy for molten salt reactor: Processing optimization, microstructure and mechanical properties

GH3539 is a most promising material for next-generation molten salt reactors (MSR) due to its excellent performance in harsh high temperature molten salt environments. To promote the application of laser welding of GH3539 alloy in the molten salt reactor, the effect of various laser welding parameters on the weld geometry was investigated, as well as the microstructure and mechanical properties of GH3539 laser welded joints. The results indicate that GH3539 alloy has good laser weldability. The weld geometry of the laser welded alloy joint is significantly affected by the laser welding parameters. After processing optimization, the optimized laser welding process parameters were obtained. The microstructure close to the fusion line is a columnar crystal growing perpendicular to the direction of the fusion line. The core of the central portion of the welded joint consists of equiaxed crystals. No apparent “softened” heat-affected zone (HAZ) was discovered in the laser-welded joints. The hardness of the weld metal (WM) is approximately 130% of the hardness of the base metal (BM). Hardness values in different areas of the WM display unique distributions due to the influence of microstructure and intergranular carbides. A small amount of tiny solidification cracking, liquidation cracking is found in welded joints. Compared to specimens at room temperature (RT), both the tensile strength and elongation dropped significantly under the circumstances of elevated temperature. All fractures are located in the BM with a brittle fracture pattern.

Simulation of temperature field and residual stress in high-power laser self-melting welding process of CLF-1 steel medium-thick plate

To mitigate the adverse effects of residual stress and deformation during high-power laser welding, this study established a finite element model based on thermodynamic conditions for high-power laser welding of CLF-1 steel for nuclear fusion applications. The temperature field and residual stress of the weld were simulated by using the composite heat source model together with Gaussian model and conical model. The results showed that the temperature field simulation was in good agreement with the real temperature field. The simulation results of the weld metal (WM) and the heat affected zone (HAZ) in the cross sections were basically consistent with those of the real cross sections. Moreover, the margin of error between the simulation results and the real data was ≤ 1.3% (the largest error ≤0.04 mm). The Von Mises equivalent stress in WM was distributed irregularly, and its largest value was ≤ 220 MPa; the equivalent stress declined with an increase in distance from the center of WM. The transverse stress distribution in the center of WM was in accordance with the vertical stress distribution, which was essentially the same as the experimental data of the vertical stress. The simulation results of deformation in the Z direction of the weld showed that the maximum deformation was about -0.2 mm at the center of the weld corresponding to the length of 300 mm. In summary, the thermal source model, combined with laser welding process parameters, can provide high-precision prediction of stress variations and deformation control during the actual welding manufacturing process of the test blanket module (TBM) structure.

Modelling and optimization of laser welding of Al2024 aluminium alloy

PurposeAluminium alloys can be used as lightweight and high-strength materials in combination with the technology of laser beam welding, an efficient joining method, in the manufacturing of automotive parts. The purposes of this paper are to conduct laser welding experiments with Al2024 in the lap joint configuration, model the laser welding process parameters of Al2024 alloys and use propounded models to optimize the process parameters.Design/methodology/approachLaser welding of Al2024 alloy has been conducted in the lap joint configuration. Then, the influences of explanatory variables (laser peak power, scanning speed and frequency) on outcome variables (weld width [WW], throat length [TL] and breaking load [BL]) have been investigated with Poisson regression analysis of the data set derived from experimentation. Thereafter, a multi-objective genetic algorithm (MOGA) has been used using MATLAB to find the optimum solutions. The effects of various input process parameters on the responses have also been analysed using response surface plots.FindingsThe promulgated statistical models, derived with Poisson regression analysis, are evinced to be well-fit ones using the analysis of deviance approach. Pareto fronts have been used to demonstrate the optimization results, and the maximized load-bearing capacity is computed to be 1,263 N, whereas the compromised WW and TL are 714 µm and 760 µm, respectively.Originality/valueThis work of conducting laser welding of lap joint of Al2024 alloy incorporating the Taguchi method and optimizing the input process parameters with the promulgated statistical models proffers a neoteric perspective that can be useful to the manufacturing industry.

Performance of ANN in predicting the depth to width ratio and tensile strength of UNS S32750 laser weld joints

The effectiveness of the pulsed mode laser weld joint is characterized by the supply of optical energy to the interface. The laser welding process parameters, such as laser power, pulse duration, travel speed and focus, determine the efficacy of the weld, which is defined by full penetration and free of pores and defects. However, expressing the relationship between various process parameters and mechanical strength is intricate due to the prevalence of non-linear relationship. The development of computational approaches aids in optimizing the laser welding parameters and reducing trial and error. Hence, the artificial neural network (ANN) model is developed, in a python environment, to predict the optimum process parameter values for a desirable depth to width ratio and maximum tensile strength of UNS S32750 laser butt weld joints. The developed model was assessed by experiments, not utilized for training. The ANN model predicts the depth to width ratio and tensile strength of the weld joints with an accuracy of 90% and less than 10% divergence from the experimental result. Furthermore, for the process, parametric conditions are: (power: 550 W, focus: –1 mm, pulse duration: 13 Hz and travel speed: 136 mm/min) to attain maximum tensile strength.

Experimental studies and optimization of process parameters in laser welding of stainless steel 304 H

The prime objective of this work is to find the best combination of parameters in laser welding of stainless-steel 304 H plates. CO2 laser welding was used to join 5 mm thick stainless-steel 304 H plates. Laser power, welding speed, and focal position were used as input parameters, and experiments were conducted on the basis of the Taguchi L27 matrix. The quality of the weld was analysed by measuring depth of penetration, bead width and hardness. The best parameter combination was found using artificial neural network and genetic algorithm. The Levenberg–Marquardt algorithm predicted output responses more accurately. A confirmatory test was carried out for the optimized parameters identified by the genetic algorithm. The percentage error between the experimental and predicted genetic algorithm values was below 6%. In comparison to the base metal, the optimized weld hardness was increased by 8%. The electron backscatter diffraction analysis of the optimized weld revealed the presence of a higher percentage of high-angle grain boundary than low-angle grain boundary.

Effect of the meltdown on thermoplastic joint produced by quasi-simultaneous laser transmission welding

This study aims to investigate the effect of the polymer pair meltdown process and mechanical properties using three different laser transparencies 20%, 30% and modulated, ranging from a minimum 27% to a maximum 47%. The cross-sections of joints were analysed with an optical microscope. Burst pressure was performed to evaluate the strength of welded joints produced with different laser welding process parameters. Welding parameters, scanning speed and meltdown were varied and their influence on the quality of the polymer joint was recorded and evaluated. With the increase of meltdown, a more molten volume of polymer can be seen in the cross-section area. It was shown that with the increase of meltdown, the formation of pores occurred due to the high energy concentration obtained within each laser scan passing across the weld seam. The decrease of burst pressure in all polymer pairs was observed with 0.33 mm and 0.34 mm targeted meltdown. Burn marks and burned lines were observed in joints with 20% laser transparency. Modulated laser transparency influenced non-homogeneous temperature distribution inside the joint, which influenced the formation of heat-affected zones (HAZ) and pores. A study of the influence of cooling time on joint formation showed that it is possible to variate total meltdown while changing cooling time until the joint is solidified. • Within the increase of meltdown, bigger weld flash occurred inside weld seam. • Peak weld strength observed at specific meltdown values. • The decrease of weld strength is influenced by defect formation inside seam. • Non-homogeneous melting, HAZ observed with modulated laser transparency polymers. • Total meltdown can be controlled by modulating cooling time.

Investigation of Strength and Formability of 6016 Aluminum Tailor Welded Blanks

The automotive industry is constantly looking for innovative techniques to produce lighter, more efficient, and less polluting vehicles to comply with the increasingly restrictive environmental regulations. One of the latest technologies, which is still developing, is based on the fabrication of the body-in-white and car parts through the stamping of aluminum tailor welded blanks. Tailor welded blanks (TWBs) are generally a combination of two/three metal sheets with different thicknesses and/or mechanical strengths, which are commonly laser butt-welded. Even though the aluminum TWBs have the main advantage of producing lightweight parts, their use is still limited by the lower formability than their parent materials and by the fact that laser welding of aluminum sheets still remains a process easily subjected to weld defects (i.e., internal porosity) and, hence, requires strict control of process parameters. This study has investigated the effects of the main laser welding process parameters (laser power, welding speed, and focus position) on the mechanical properties and formability of aluminum TWBs made of the 6xxx series. The research results show that the welding conditions highly influence the weldability of such alloys. Heat input over 70 J/mm is responsible for excessive porosity and molten pool (and consequent root concavity), which are responsible for the lowest mechanical strength and formability of joints. Differently, low amounts of imperfections have a limited influence on the mechanical behaviors of the TWB joints. Overall, a narrow weldability window is required to ensure welded joints with proper strength and limited or no porosity.

Measurement and simulation of residual stresses in laser welded CFRP/steel lap joints

In light of the demand for reducing the emission of climate-damaging gases such as CO2, it is very important to apply lightweight materials in the aerospace and automotive industries. In the past years, hybrid structures made of carbon fiber reinforced plastics (CFRP) and metals received high attention from numerous industries. Laser welding is an advanced approach for bonding dissimilar materials. However, in the welding process, residual stresses are induced in the joined part, which influence the mechanical performance of the bonded components. In the present work, residual stresses in laser welded CFRP and steel joints are experimentally determined using the hole drilling method (HDM) and numerically analyzed by thermal elastic–plastic finite element analysis. The non-uniform residual stress distribution through the thickness direction of the CRRP and steel plates can be successfully measured when the anisotropic material properties in CFRP are considered. Moreover, a numerical simulation was carried out for analyzing the residual stresses in the laser welded CFRP/steel joints, particularly their distribution characteristics at the CFRP/Steel interface. Specific discussions focus on the residual stress formation mechanism and the effect of laser welding process parameters on the residual stresses through experimental tools and numerical simulations.

Optimization of Laser Beam Welding Parameters for 90/10 Cupronickel Alloy Welds Using Taguchi Method

Abstract This study is to identify the most important control elements that will result in improve the tensile strength of Laser Beam Welded Cu-Ni 90/10 alloy joints. The different laser welding process parameters and levels were used for joining of Cu-Ni alloy. The process parameters like Laser Power (LP), Shielding Gas (argon) (SG), Focal Position (FP), & Welding Speed (WS) were chosen in the experimental study. The welding was carried on 4mm thick plate as per Taguchi’s experimental design. The mechanical properties were evaluated and microstructural observations were carried out. It was discovered that highest tensile strength of 234 MPa & hardness of 83 Hv were obtained which has 90 % and 87 % of the base material. The most influential optimal process parameters were determined using S/N analysis and the percentage contribution of each process parameter was estimated using ANOVA. It was found that laser power was influential parameter with a 64 % contribution in obtaining highest strength of laser welded joints. The experimental values and the results of the confirmation experiments were in good agreement.

Improvement of welding stability and mechanical properties of galvanized DP800 steel lap joint by high-speed tandem beam laser

Dual beam laser welding has shown promise to improve the weldability of galvanized dual phase steels. In this study, the lap joints of galvanized dual phase steel were welded with tandem beam laser at speed up to 100 mm/s. The power ratio for the dual beams was set to 50%:50%, 40%:60%, 30%:70%, and 20%:80%, respectively. A high-speed camera was used to observe the dynamic process of zinc vapor, molten pool, and keyhole behaviors under different welding conditions. The corresponding metallographic and mechanical analysis were conducted to reveal the effects of variable welding thermal cycles on the microstructures and properties of the welded joints. The results indicate that the fusion zone (FZ) is composed of blocky-lath martensite, whereas the heat-affected zone (HAZ) is characterized by the lath microstructure containing tempered martensite (TM) and ferrite (F). The power ratio of dual beams significantly affects the microstructures and hardness profiles of welded joints. It also influences the zinc-vapor and molten pool dynamic behaviors, thus affecting the weld bead formation. The weight of spatter decreases with the decrease of leading beam power in tandem beam laser welding process. In addition, the mechanical properties of the welded lap joints are significantly affected by the high-speed tandem dual beam laser welding process parameters. The failure load of tensile-shear testing reaches the maximum value when the beam power ratio is 30%:70%.

Multi-objective optimization of laser welding process parameters: The trade-offs between energy consumption and welding quality

Laser welding, a key and competitive technology for advanced industrial manufacturing is powered by energy. With increasing attention to energy management and environmental protection in manufacturing, reducing energy consumption is imperative. However, the traditional optimization of laser welding has been mainly focused on welding quality without considering the total energy consumption of all components. Thus, this paper researches the relationship between welding quality and energy consumption by optimizing process parameters during the 2 mm thickness 6061 aluminum alloy laser welding. Firstly, a three-factor, three-level experiment using Central Composite Design (CCD) is constructed. Secondly, Kriging models are employed to construct the models between process parameters and objectives. Finally, the Non-dominated Sorting Genetic Algorithm-III (NSGA-III) is utilized to minimize energy consumption while maintaining good welding quality. The study shows that compared to the initial scenario, optimization can reduce energy consumption while increasing welding quality.