Friction Stir Welding Process Parameters Research Articles

Investigation of The Weldability of PLA Plus Sheets with Different Infill Ratios by Friction Stir Welding

Although the joining processes of plastics are typically carried out through welding, adhesive bonding, or mechanical fastening elements, the production of complex and large parts often requires welding technology. In this study, the effect of part infill ratio (20%, 40%, 60%, 80%, and 100%) on the welding strength of 3D printed PLA Plus parts was evaluated through friction stir welding (FSW). Tensile tests and temperature measurements were carried out to examine the effects of friction stir welding process parameters (feed rate: 50 and 100 mm/min and rotational speed: 1000 and 1500 rpm) on the structure and mechanical properties of friction stir welding. Moreover, visual inspections were performed to detect defects in the weld zone. Compared to the PLA Plus samples given as reference according to the infill ratios, the highest welding strengths were obtained at 80%, 60% and 100% infill ratios (29.4 MPa, 17.47 MPa and 41.12 MPa and 112.38%, 97.48%, 87.04% efficiency, respectively). As a result, it was determined that at low infill ratios (20% and 40%), the weld quality was negatively affected, and a surface tunnel defect occurred in the weld zone. It has been determined that the weld quality in FSW is significantly affected by the temperature occurring during the process. The study has shown that parts printed at different infill ratios, especially on a 3D printer, can be combined with friction stir welding and that the efficiency of the welding process can be increased by optimizing the infill ratios.

Efficiency Improvement of Friction Stir Welding Parameters on AZ91 Magnesium Alloy Joints

Abstract: Friction Stir Welding (FSW) is a solid-state welding that permits an intensive formof parts and geometries to be welded with great nature of joints. The use of high-quality Magnesium alloys is extending in shipbuilding industry, particularly for the advancementof naval warships, cruise ships, littoral surface craft and merchant ships. FSW advancementhas been seemed to have various focal points for the exploitation of Magnesium alloys structures, as it is a minimal effort welding process. The objective is to come across the optimum levels of the process parameters in which it yields maximum tensile strength andbetter hardness. A three-factor, three-level design is utilized for optimizing the FSW process parameters and a Taguchi L9 orthogonal array experimental set up is used to anticipate the responses. The system parameters considered are Rotational speed, Transverse speed and the Tool tilt angle. The Friction stir welding is processed for butt joining of Magnesium alloys (AZ91) plates with 6 mm thickness. Tensile testing is attempted on dog-bone kind test specimen for Magnesium alloys. Analysis of Variance (ANOVA) has been used to analyze the effect of different parameters regarding the responses. The microstructural attributes of the welded segments, including base metal, heat affected zone (HAZ), Thermo Mechanically Affected Zone (TMAZ) and Stir Zone (SZ) are examined through Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray (EDX) analysis carried out to quantify the chemical element allocation at the weld interface. The observed optimum condition for Magnesium alloys (AZ91) is 560 rpm, 60 mm/min and 1 degree.

Behavior of microstructure and mechanical properties in the stir zone of friction stir welded ME21 magnesium alloy

In this work, Friction Stir Welding (FSW) of magnesium alloy ME21 in a T-profile is performed with a relatively higher welding speed than usual in this material. The FSW process parameters, i.e., rotational speed and welding speed, are investigated focused within its inherent microstructural and mechanical properties on the stir zones of the welded joints. The concept of a Stribeck Curve in tribological systems, is transferred to FSW to explain the transition between insufficient and full plasticization of the material. The stir zone presented a strong grain refinement due to the activation of dynamic recrystallization along with a completely changed crystallographic texture and orientation due to FSW. The hardness is overall improved, while the ductility and tensile strength were reduced. The microstructure and texture in the stir zone were not strongly influenced by changes in the welding parameters.

Experimental Modeling and Multi-Response Optimization in Friction Stir Welding Process Parameters of AA2024-T3 Using Response Surface Methodology and Desirability Approach

Experimental Modeling and Multi-Response Optimization in Friction Stir Welding Process Parameters of AA2024-T3 Using Response Surface Methodology and Desirability Approach

Development of FSW Process Parameters for Lap Joints Made of Thin 7075 Aluminum Alloy Sheets.

The article describes machine learning using artificial neural networks (ANNs) to develop the parameters of the friction stir welding (FSW) process for three types of aluminum joints (EN AW 7075). The ANNs were built using a total of 608 experimental data. Two types of networks were built. The first one was used to classify good/bad joints with MLP 7-19-2 topology (one input layer with 7 neurons, one hidden layer with 19 neurons, and one output layer with 2 neurons), and the second one was used to regress the tensile load-bearing capacity with MLP 7-19-1 topology (one input layer with 7 neurons, one hidden layer with 19 neurons, and one output layer with 1 neuron). FSW parameters, such as rotational speed, welding speed, and joint and tool geometry, were used as input data for ANN training. The quality of the FSW joint was assessed in terms of microstructure and mechanical properties based on a case study. The usefulness of both trained neural networks has been demonstrated. The quality of the validation set for the regression network was approximately 93.6%, while the errors for the confusion matrix of the test set never exceeded 6%. Only 184 epochs were needed to train the regression network. The quality of the validation set was approximately 87.1%. Predictive maps were developed and presented in the work, allowing for the selection of optimal parameters of the FSW process for three types of joints.

Intelligent Prediction of FSW Physical Quantity and Joint Mechanical Properties

Friction stir welding (FSW) process parameters influence welding temperature field and axial force, which affect welding strength. At present, how the FSW process parameters of aluminum alloy 2219-T8 thick plates influence process physical quantity and how the process physical quantity changes the tensile strength about the welded joint are unknown. We focus on the intelligent prediction of FSW temperature, axial force, and mechanical properties, to provide a basis for FSW process control of aluminum alloy 2219-T8 thick plate. Firstly, we conducted the FSW experiment of aluminum alloy 2219-T8 thick plate. Then, we input the welding process parameters, set up a prediction model by particle swarm optimization-back propagation (PSO-BP) neural network to predict the peak temperature and axial force. Finally, we input the peak temperature and axial force, use genetic algorithm-back propagation (GA-BP) neural network to establish a weld tensile strength estimation model, and comply with the prediction of tensile strength.

Ispitivanje i optimizacija površine zavara i mehaničkih performansi termoplastičnih delova proizvedenih aditivnom proizvodnjom i zavarenih zavarivanjem trenjem

This study presents an experimental investigation into the weldability of ABS M30 (acrylonitrile butadiene styrene) plates produced by Additive Manufacturing (AM) using Friction Stir Welding (FSW). The effects of FSW process parameters on the yield stress and their optimal levels were determined using the Taguchi method. The optimal welding parameters were found to be a 16 mm tool shoulder diameter, 800 rpm tool rotation speed, and 10 mm/min traverse speed. The weld area of each sample welded using FSW was examined at a macroscopic level. The direction of tool rotation significantly affects the quality and strength of the FSW. When the FSW was performed with a clockwise rotation of the welding tool, a perfect weld could not be achieved. The tunnel effect resulted in gaps in the weld area of the samples at high rotation speeds. Differences were observed in the density between the weld area of the samples and the main parts.

Effect of process parameters on friction stir welding of aluminium alloy AA6082–T6 with an interlayer using response surface methodology

In the present study, the effects of variation of process parameters on the mechanical properties of friction stir welded A6082–T6 aluminium alloy joints with Zinc (Zn) interlayer are experimentally investigated. Four process parameters, viz. rotational speed, welding speed, interlayer thickness and tool pin diameter are selected to fabricate the Friction Stir Welding (FSW) joints. After filling the Zn particles into the gap maintained between the plates, FSW is performed using different process parameters. Thereafter, tensile and impact strength tests are performed to evaluate the performance of the joints. It is analyzed that the tensile and impact strength of the joints vary from 121 to 197 MPa and 6 to 17 J, respectively. Subsequently, mathematical models are developed using Response Surface Methodology (RSM) to predict the effect of FSW process parameters on the tensile and impact strength of joints. Analysis of Variance (ANOVA) is used to check the level and degree of direct effect of process variables on the tensile and impact strength of the joints. It is observed from the results that tool rotational speed is the most influential process parameter, which enhances the mechanical properties of FSW joints, whereas an increase in welding speed reduces the mechanical properties of the joints.

A comparative study of multiple-criteria decision-making methods for selecting the best process parameters for friction stir welded Al 6061 alloy

The selection of welding process parameters is a tedious operation that demands the process evaluation. Multi criteria decision-making strategies for assessing friction stir welding (FSW) process parameters are scanty. Therefore, a comparative study between five different multi-criteria decision-making methods was applied within friction stir welding process to show the deviations in the ranking of the alternatives. The goal is to find the welding parameters (including rotation speed, shoulder diameter, and travel speed) that result in the highest performance scores or rankings for the considered responses, such as ultimate tensile strength, hardness, and surface roughness. In the following, different decision-making strategies (including TOPSIS, GRA, hybrid GRA-TOPSIS, CoCoSo, and MACROS) are applied to calculate the weight of all different decision-making using entropy. The proposed methods in this study are validated by representing the accurate decision maker’s preferences and consideration of uncertainty. The decision-makers choose GRA-TOPSIS and TOPSIS as the best approach with higher efficiency. GRA was determined to be more time-consuming and to have the most variety of outcomes, whereas CoCoSo and MACROS were unable to produce a definite best result. The study is highly promising for researchers and machining specialists to produce quality friction stir welds.

Effect of friction stir welding on microstructure and foaming mechanism of rolled-state anisotropic powder

Friction stir welding (FSW) has a significant impact on welding aluminum foam sandwich (AFS) precursor. Yet, the understanding of the microstructure and foaming process on rolled-state powder of welded precursor remains limited. This study exploited the single-pass double-sided forming welding approach to weld the AFS precursor, while the impact of different process parameters of FSW on the microstructure of rolled-state powder was evaluated. Meanwhile, the foaming process of anisotropic powder at different directions was observed in-situ using synchrotron radiation. The results display that FSW transforms gap-like voids, which were ∼20 µm in width and 100–400 µm in length, into circular voids with a diameter of ∼6 µm in the powder at the weld zone (WZ). The welding process eliminates powder agglomeration aggregation and increases the relative density (>97%) of rolled-state powder. However, the low thermal conductivity of the rolled-state powder (117 W·m−1·K−1) leads to a tunnel defect at the root of the WZ. In addition, in-situ observation experiments of the foaming process found that the bubble nucleation of rolled-state powder exhibits anisotropic characteristics, and the welding process causes a transition in the types of bubble nucleation in the WZ region. This study demonstrates the feasibility of improving the anisotropy of powders caused by processing methods to obtain an isotropic pore formation and foam expansion by FSW technology.

Influence of friction stir welding process parameters and statistical behaviour of the novel interlock aluminum alloys joint with SiCp reinforcement

Influence of friction stir welding process parameters and statistical behaviour of the novel interlock aluminum alloys joint with SiCp reinforcement

Optimization of process parameters for producing AA6061/SiC nanocomposites by friction stir processing Optimization of process parameters for FSW AA7075/TiC, B4C, Al2O3 nano Hybrid composites by Taguchi technique


 
 
 
 A significant area of research now being pursued by the foundry industry is how to enhance the mechanical properties of aluminium alloys by reinforcing them with micro ceramic particles. The mechanical and Microstructural studies of commercial AA 7075 stir die castings reinforced by various weight ratios of titanium carbide (TiC), boron carbide (B4C), and aluminium oxide (Al2O3) have been examined in the current study. Further, friction stir welding (FSW) process has been carried out based L16 Orthogonal Array (OA). Optimal decision making approach for the improvement of Friction Stir Welding (FSW) process was performed by Taguchi method. Investigations were conducted on the effects of three variables on UTS, including rotating speed, transverse speed and tilt angle. The maximum ultimate tensile stress was found to be around 162 M Pa for sample 8 (1.5 wt% TiC, 0.5 wt% B4C and 0.8 wt% Al2O3) welded at speed 900 rpm, feed 45 mm/min, and Tilt angle 2.50.
 
 
 

Multi objective Optimizations of friction stir welding process parameters for reinforcement of copper particles in aluminum alloy using Taguchi based grey relational analysis (GRA) and ANOVA.

In this paper, optimize process parameters of friction stir welding for reinforcement of copper particulate in between aluminum alloys. It is to boost the thermal conductivity and mechanical properties of base metals. Two dissimilar aluminum alloys with different mechanical properties .AA6061-AA6063. successfully joined. In addition, the introducing copper particles of 325 mesh size in between aluminum alloy 6061 and 6063. It is a direct application of rotating non-consumable friction stir welding tool plunged for reinforcement. Introduction of a copper particle in between aluminum alloy is a unique system in the solid-state welding process. Taguchi method as an optimization tool used to design process parameters. Afterward, welding samples were cut in the desired size and progressed for a further test such as tensile and hardness test. Finally, it is observed to have improved mechanical strength in minimum spindle speed i.e.1000 rpm and welding speed 20 mm/min. Study also shows feasibility of GRA, Hypothesis .Z-test. test and ANOVA with Taguchi technique.

Thermomechanical Modeling of Material Flow and Weld Quality in the Friction Stir Welding of High-Density Polyethylene.

A thermomechanical model of the friction stir welding (FSW) of high-density polyethylene (HDPE) was developed by incorporating a Coupled Eulerian-Lagrangian (CEL) approach. A Johnson Cook (JC) material model of HDPE was developed through experimentally generated strain-rate- and temperature-dependent stress strain data. Two sets of FSW process parameters with minimum and maximum weld defects were numerically modeled. The numerically calculated temperature distribution, material flow and flash and potential defects were validated and discussed with the experimental results. Tracer particles allowed to visualize the material movement during and after the tool had traversed from the specified region of the workpiece. Both numerical models presented similar maximum temperatures on the upper surface of the workpiece, while the model with high traverse speed and slow rotational speed had narrower shoulder- and heat-affected zones than the slow traverse, high rotational speed model. This contributed to the lack of material flow, hence the development of voids and worm holes in the high traverse speed model. Flash and weld defects were observed in models for both sets of process parameters. However, slow traverse, high rotational speeds exhibited smaller and lesser weld defects than high traverse, slow rotational speeds. The numerical results based on the CEL approach and JC material model were found to be in good agreement with the experimental results.

Statistical modelling and optimization of FS-welded 6061-T651 Aluminum alloy

An RSM-based experimental design, mathematical modelling and statistical optimization of friction stir welding process parameters was studied. A quadratic fitting model developed from a five-leveled four-factor parametric setting predicted the Ultimate Tensile Strength (UTS) of the welded AA6061- T651 joints. Statistical analysis at 95% Confidence Interval using ANOVA validated the conformity of the developed model with experimental data and also verified the adequacy of the model for UTS prediction and optimization. Results showed that the model was statistically significant (p<0.0001) with no notable lack of fit with the four parameters and their squared terms also significant statistically. The numerical optimization resulted to an optimum UTS of 166.32MPa from rotational speed, traversing speed, tool tilt angle and axial load values of 1293.641rpm, 48.467mm/min, 1.888° and 4.720kN, respectively with a desirability of 0.944. Also, 2D contour and 3D surface plots showed that the four parameters made decreasing effects on the UTS after reaching their optimized UTS. Driving forces for high UTS were: sufficient heat generation for plastic deformation, effective material coalescence, appropriate extrusion of molten material towards the trailing edge, adequate heat and mass transfer to control grain coarsening, void and flash formations. With an SN-ratio of 45.963 and low coefficient-of-variation of 1.11%, the conformity of the predicted and adjusted regression coefficients (R²) of 0.9619 and 0.9868 respectively supported by the confirmatory test and diagnostic plots showed a strong correlation between the experimental and predicted results. These demonstrated that the developed model was sufficient for predicting and optimizing the UTS of Friction Stir Weld (FSW) AA6061T651 plates.

Establishment of empirical relations amidst mechanical attributes of friction stir welded distinctive alloys of Mg and optimized process parameters

This experimental investigation aims to formulate quadratic regression based empirical model taking into account the parameters of friction stir welding (FSW) process for predicting the optimized process parameters to maximize the response (i.e., ultimate tensile strength) of the distinctive alloys of Mg joints. Parameters of FSW process taken into consideration includes tool’s traverse speed, axial force and rotational speed of tool and response being the fabricated joint’s tensile strength. A central composite rotatable category 3–factor, 5 level design based matrix was formulated and response surface methodology was used to obtain regression based models, to generate contour plots and to visualize the interactive impacts of parameters on the joint’s tensile strength. Formulated quadratic regression based model was validated employing analysis of variance. Comparison amidst the realistic and anticipated values of the response announced the superior fitting accuracy of the formulated quadratic model. For a constant tool’s rotational speed (of 1000 rpm to 1250 rpm), the tensile strength was observed to be highly sensitive to the axial force values than the tool traverse speed values. Mean tensile strength of the friction stir welded AZ31B, AZ80A, AZ91C, AM50A and ZK51A-T5 Mg joints during the employment of optimized process parameters were found to be 217.5 MPa, 251.4 MPa, 231.9 MPa, 192.1 MPa and 173.2 MPa respectively, thereby exhibiting perfect agreement with the anticipated values.

Hybrid heuristic methods exercising to optimize the friction stir welding process parameters for improving the prepared butt joints mechanical properties

Purpose The weld joint mechanical properties of friction stir welding (FSW) are majorly reliant on different input parameters of the FSW machine. The study and optmization of these parameters is uttermost requirement and aim of this study to increase the suitability of FSW in different manufacturing industries. Hence, the input parameters are optimized through different soft computing methods to increase the considered objective in this study. Design/methodology/approach In this research, ultimate tensile strength (UTS), yield strength (YS) and elongation (EL) of FSW prepared butt joints of AA6061 and AA5083 Aluminium alloys materials are investigated as per American Society for Testing and Materials (ASTM E8-M04) standard. The FSW joints were prepared by changing the three input process parameters. To develop experimental run order design matrix, rotatable central composite design strategy was used. Furthermore, genetic algorithm (GA) in combination (Hybrid) with response surface methodology (RSM), artificial neural network (ANN), i.e. RSM-GA, ANN-GA, is exercised to optimize the considered process parameters. Findings The maximum value of UTS, YS and EL of test specimens on universal testing machine was measured as 264 MPa, 204 MPa and 14.41%, respectively. The most optimized results (UTS = 269.544 MPa, YS = 211.121 MPa and EL = 17.127%) are obtained with ANN-GA for the considered objectives. Originality/value The optimization of input parameters to increase the output objective values using hybrid soft computing techniques is unique in this research paper. The outcomes of this study will help the FSW using manufacturing industries to choose the best optimized parameters set for FSW prepared butt joint with improved mechanical properties.

Analysis of sensitivity and formulation of empirical relationship between parameters of FSW process and tensile strength of AZ80A Mg alloy joints

In this research paper, an endeavour was made to devise empirical relations amidst the process parameters of friction stir welding (FSW) and tensile relevant strength of AZ80A Mg alloy joints, based on a 6 parameters—5 levels based central composite design (CCD). Mathematical equations illustrating the impact of process parameters of FSW were formulated based on quadratic regression based analysis to optimize the parameters for attaining superior tensile strength and sensitivity related equations were established from these numerical models. A detailed sensitivity characteristic relevant map for the FSW of AZ80A Mg alloys was established forecasting the fine tuning related prerequisites of the employed FSW parameters. Coefficient of determinant (R2) announced that 99.062% of the overall variability was described by the formulated model and only lower than 1% of the overall variations was not justified by the model. Predicted R2 was also in perfect agreement with the adjusted R2 and announced the model’s capability to demonstrate 95.43% of the variability in the generated data. Highest value of tensile relevant strength (80.77% of the parent metal) was exhibited by the AZ80A Mg alloy joint fabricated under optimized parameters. Tensile relevant strength of AZ80A Mg joints was observed to be highly sensitive to traverse speed of the employed tool.

Process parameters for friction stir welding on A319 aluminium alloy using hybrid technique for order of preference by similarity to an ideal solution and grey relational analysis multi-criteria decision-making method

The major goal of this study is to look into friction stir welding process parameter optimization with the combined decision model, the tensile strength of the best parameter combinations is higher. The recommended hybrid strategy for order preference by similarity to ideal solution (technique for order of preference by similarity to an ideal solution) and grey relational analysis method are used to discover the optimum process parameters. It is also suitable for welding aluminium alloy A319 is Tool rotational speed (r/min), Feed for welding (mm/min), and diameter of tool pin (mm) are all considered while using the friction stir welding process. This operation is primarily implemented through various experiments using Taguchi L9 orthogonal arrays. To this problem, the (technique for order of preference by similarity to an ideal solution) and (grey relational analysis) models are used. Hence, this technique has demonstrated the technology used to identify multi-criteria decision-making in friction stir welding and process parameter optimization for the best results.

CHARACTERISTIC OF FRICTION STIR WELDING WELD JOINT OF AA 6061 ON INITIAL TEMPERATURE DIFFERENCE

Friction stir welding (FSW) is a solution to overcome the problems of AA 6061 welding. When the initial temperature T0 of the material is increased during the FSW process while the FSW process parameters are kept constant then FSW welding parameter value can be lowered. T0 was varied by Troom temperature, 50 0C, 75 0C, 100 0C and 125 0C. The weld joint design form is a square butt joint. By using this approach the higher the T0, with the FSW parameter being kept constant, produce the higher the welding peak temperature and cooling rate, the smaller and smoother the metal grain structure in the weld nugget, TMAZ and HAZ, the higher the hardness of the weld nugget and the higher the tensile strength eventough welding defects in the form tunneling, kiss bond, and void are still observed.