Range Of Welding Parameters Research Articles

Digital twin modeling method of the temperature field of thermo-compression bonding blade based on generative adversarial networks

In this paper, a novel method of using deep learning to construct a digital twin of the thermos-compression bonding blade`s temperature field is presented. Usually, a heat transfer model based on numerical analysis can calculate the heat distribution in the welding process, but its complex modeling process and heavy computational effort are not appropriate for the deployment of the digital twin concept. The approach proposed in this paper is distinctive because it directly converts the collected process sensor data into the bonding blade's temperature field images and the bonding surface's temperature distribution curves for monitoring the welding process. This is achieved by training the generator and discriminator of the conditional depth convolutional generative adversarial network separately. The network is then capable of predicting the bonding blade's heat distribution within a certain range of welding parameters. Compared to methods based on numerical simulation, this approach is far more effective. Training and testing datasets were created to assess the suggested method's efficacy. Multi-scale structural similarity index, structural similarity index, peak signal-to-noise ratio, difference hash and mean absolute error were used to evaluate the simulations' quality. The results show that the simulation's results and the actual data agree quite well. The temperature changes that occur during the welding process may be quickly and accurately simulated using the proposed technology.

Process parameter analysis of double pass friction stir composite welds

ABSTRACTThe novelty of the research work stems from the investigation of double pass FSW-friction stir welding on 6061 T6 and 7075 T651 alloys of aluminum matrix reinforced/supplemented with nano h-BN. Preparation of weldments was accomplished by deploying a range of welding parameters specifically tool spindle speed, tool traverse feed, and tool profile. L20 orthogonal array based on a CCD-Central composite design was implemented for experimentation. Microstructural and grain analysis with the performance of parameters on strength and hardness property was detailed. Regression models were developed and optimized based on RSM-Response surface methodology and GRA-Grey relational analysis. The optimal conditions favoring improved tensile strength and hardness based on RSM were realized at 848 rpm, 36 mm min−1, and with a tool profile being cylindrical. A state of consistency prevails between the predicted and experimental responses. Analysis based on GRA yields optimal conditions that fairly corroborate with RSM.

Non-destructive evaluation of the friction stir welding process, generalizing a deep neural defect detection network to identify internal weld defects across different aluminum alloys

Friction stir welding (FSW) is a solid-state welding process, which has significantly disrupted welding technology particularly for aluminum alloy applications. Due to its high-quality welds in all aluminum alloys, comparatively low heat input with high energy efficiency and ecological friendliness, FSW is used in a rapidly growing number of applications. Currently, destructive and non-destructive testing methods are attached as a separate process step to verify weld seam quality, detecting imperfections late in production and requiring costly rework or scrapping of the assembly. Various studies have shown the possibility of using deep neural networks (DNN) to evaluate weld quality and detect welding defects based on recorded data. In this study, conducted within the scope of RWTH Aachen’s Cluster of Excellence, Internet of Production, recurrent neural networks (RNN), and convolutional neural networks (CNN) were successfully trained to classify FSW force data sets, generated while joining different aluminum alloys over a wide range of welding parameters. For internal weld defects bigger than 0.08 mm, detection accuracies over 95% were achieved using bidirectional long short-term memory (BiLSTM) networks when limited to a single alloy and thickness. The classification accuracy dropped to ~ 90% when using multiple alloys and sheet thicknesses. The comparison between different network types’ classification accuracy as well as their ability to generalize the defect detection across different welding tasks with varying sheet thicknesses, respective welding tools, and different Al alloys is shown. The systems aim at offering a reliable and cost-efficient quality monitoring solution with a wide range of applicability, increasing the acceptance of the friction stir welding process as well as confidence in the resulting weld seam quality.

Experimental investigation on microstructural characterization and mechanical properties of plasma arc welded Inconel 617 plates

Abstract Welding of Inconel is a difficult task due to its tendency to crack and posing intricacies to the welder. However, it is extensively used in applications where resistance to oxidation at elevated temperatures is required. Therefore, it is important to note that the welding of Inconel alloys is demanding. Under such circumstances, one has to automate the welding of Inconel 617 alloy to eliminate some of the process uncertainties. Plasma arc welding (PAW) is a highly non-linear process that can be automated easily, and it can provide more focussed arc to weld the high strength and creep-resistant alloys. In the present research, PAW process is employed on 2 mm thick Inconel 617 plates by varying the key process parameters, such as welding current and welding speed. Initially, bead on plate (BoP) experiments were conducted to determine the suitable range of welding parameters to weld the super alloy. Subsequently, butt welding of the plates was performed based on the results of BoP welding. Furthermore, a study was conducted to determine the influence of the welding process parameters on the microstructural and mechanical properties of the butt joints.

Stress crack resistance of unaged high-density polyethylene geomembrane fusion seams

The stress crack resistance (SCR) of high density polyethylene (HDPE) geomembrane (GMB) fusion seams is examined for two 1.5 mm HDPE GMBs and a range of welding parameters. Results are reported for both unnotched and notched seams as well as their corresponding sheet material. Unnotched seam SCR specimens are shown to preferentially initiate craze formation at the terminating edge of the squeeze-out bead, while incorporating potentially degraded areas, such as the seams heat-affected zone (HAZ), within the slow crack growth region of the specimen. In the short-term, little variation was observed between the majority of seams for the nine welding parameter combinations examined, with an average normalized seam SCR value (normalized with respect to the unnotched sheet SCR) of 0.3 ± 0.1, or about 30% of the SCR of the unnotched sheet. It is shown that squeeze-out geometry plays an important role in the SCR of fusion seams. Seams with weld track rippling, a known qualitative indication of overheating, were found to have average unnotched SCR values 45% lower than smooth weld track seams. Deleterious squeeze-out geometries are identified to provide a framework through which CQA engineers and researchers can more readily identify ‘higher risk’ seams with respect to stress cracking.

Effects of Key Processing Parameters of Continuous Drive Rotary Friction Welding on Thermal Characteristics of Similar and Dissimilar Joints

In this research study, numerical modeling was present to describe the effect of key processing parameters of continuous drive rotary friction welding (CDRFW) on thermal characteristics of similar aluminum alloy joint and dissimilar aluminum alloy /low carbon mild steel joint, using (ANSYS). A mathematical model was made to describe the heat generated in the workpiece due to the frictional force and the plastic deformation, and the heat transfer throw workpiece was described based on the Fourier law of heat conduction. The parameters were: Frictional pressure (P1), forging pressure (P2), frictional time (t1), forging time (t2), and rotational speed (N). A range of welding parameters was taken. The results show that with increases in welding parameters, the welding temperature at the interface region and the axial shortening will increase for both similar and dissimilar joints. For similar and dissimilar joints, frictional pressure and rotational speed have the most effect on maximum temperature at the interface, frictional time affects less while forging pressure and forging time have no effect on maximum temperature at the interface. For similar and dissimilar joints the most influential parameter on axial shortening was frictional pressure, with little effect for forging time.

Deep learning approaches for force feedback based void defect detection in friction stir welding

The Friction Stir Welding (FSW) process is known as a solid state welding process comparably stable against external disturbances in its steady state. Therefore, the process is commonly applied with fixed welding parameters utilizing axial force control or position control strategies. External and internal process disturbances, introduced by the workpieces, gap tolerances, tool wear or machine/tool inadequacies are rarely monitored and no conclusion towards the weld seam quality is drawn. In most applications the sole process monitoring feature is the axial force and quality control measures are often only applied to external weld seam features. Based on prior analytic process analysis and quality models based on analytic algorithms, machine learning approaches are employed to find suitable quality criteria to detect internal weld seam defects (void defects) over a wide range of welding parameters. The recorded welding force data is examined using Long Short-Term Memory (LSTM) Networks, Bidirectional Long Short-Term Memory (BiLSTM) Networks and different versions of Convolutional Neural Networks (CNN), differing in Layer architecture and Node count (and thus resulting complexity). In an effort to reduce data and speed up development and training, manual feature extraction was performed. Features were selected based on the cyclical nature of the FSW-process and prior research into in-plane process force data quality relevancy. The features as well as raw recorded force data were used to train previously mentioned networks. Overall the viability of the approaches was shown by a high rate of correct void defect classification, with CNNs exceeding 93% test set classification rate. Network training had to be closely monitored as a small dataset and large number of input features increased the risk of overfitting.

Root formation and mechanical properties in laser keyhole welding of 15 mm thick HSLA steel

Deep penetration laser welding is promising in joining thick (> 10 mm) steel sections. Focused laser beam by drilling vapour cavity, the keyhole, generates deep and narrow welds. Full penetration single-pass joining has a persistent problem with root quality where humping is one of the most frequent imperfection. This strongly hampers the use of high-power laser for thick plate welding. A 16 kW disk laser was used for single-pass welding of 15 mm thick plates in a butt joint configuration. Root humping occurred within a wide range of welding parameters. This provides narrow processing window. By adding an arc source to the laser beam process, the tendency of root humping increases. To achieve humping-free welds and consistent root quality over length, a delicate balance of process parameters is required. High heat input (> 0.50 kJ/mm) was positive to achieve a combination of low hardness (< 325 HV) and good Charpy toughness at -50 °C (> 50 J).

Mechanical properties and microstructure of additively manufactured stainless steel with laser welded joints

Powder bed fusion (PBF) is a commonly employed metal additive manufacturing (AM) process in which components are built, layer-by-layer, using metallic powder. The component size is limited by the internal build volume of the employed PBF AM equipment; the fabrication of components larger than this volume therefore requires mechanical joining methods, such as laser welding. There are, however, very limited test data on the mechanical performance of PBF metal with laser welded joints. In this study, the mechanical properties of PBF built 316L stainless steel parts, joined together using laser welding to form larger components, have been investigated; the microstructure of the components has also been examined. 33 PBF 316L stainless steel tensile coupons, with central laser welds, welded using a range of welding parameters, and with coupon half parts built in two different orientations, were tested. The porosity, microhardness and microstructure of the welded coupons, along with the widths of the weld and heat-affected zone (HAZ), were characterised. The PBF base metal exhibited a typical cellular microstructure, while the weld consisted of equiaxed, columnar and cellular dendrite microstructures. Narrow weld regions and HAZs were observed. The PBF base metal was found to have higher proof and ultimate strengths, but a similar fracture strain and a lower Young’s modulus, compared with conventionally manufactured 316L stainless steel. The strengths were dependent on the build direction – the vertically built specimens showed lower proof strengths than the horizontal specimens. The laser welds generally exhibited lower microhardness, proof strengths and fracture strains than the PBF base metal which correlated with the observed structure. This work has demonstrated that PBF built parts can be joined by laser welding to form larger components and provided insight into the resulting strength and ductility.

Imperfections and Modelling of the Weld Bead Profile of Laser Butt Joints in HSLA Steel Thin Plate

In many applications that use high strength steels, structural integrity depends greatly on weld quality. Imperfections and the weld bead geometry are influencing factors on mechanical properties of the welded joints but, especially in the fatigue strength, they cause a great decrease. The proper knowledge of these two factors is important from the nominal stress approach to the fracture mechanics approaches. Studies concerning the profile and imperfections of the weld bead in laser welding for thin plates of high strength steels are scarce. In this work, these two aspects are covered for five series single and double-welded joints, butt joints in a 3 mm thick HSLA steel, welded in a small range of welding parameters. The actual profiles captured with profilometer were modeled with proposed geometric parameters achieving an adequate fit with values of the coefficient of determination ℜ2 greater than 0.9000. Description of imperfections includes the distributions of porosity and undercuts. The evaluation of the weld quality, taking as guide the ISO 13919-1 standard determined B and D levels for the welded series while based on the stress-concentrating effect, showed a greater detriment in those series with undercuts and excessive penetration. The analysis of variance validated the results of the different combinations of laser welding parameters and showed, for the factorial experimental design, a more significant effect of the welding speed.

Friction stir lap welding thin aluminum alloy sheets

AbstractIn this work, thin aluminum alloy sheets with thickness of 0.8 mm were friction stir lap welded using small shoulder plunge depths of 0 and 0.1 mm. The joint formation, microstructure and mechanical properties were investigated. Results show that voids appear inside the stir zone when the small plunge depth of 0 mm is used because the tool shoulder cannot exert a good material-collecting effect at such low plunge depth. A plunge depth of 0.1 mm causes tight contact between the shoulder and the material and thus results in good material-collecting effect, which is helpful to eliminate the void. Sound joints are attained at a wide range of welding parameters when using the shoulder plunge depth of 0.1 mm. No crack is observed inside the bonding ligament. The joints own higher failure loads when the retreating side (RS) of the joint bares the main load during the lap shear tests. The shear failure load first increases and then decreases with increasing the rotating and welding speeds, and the maximum failure load of 6419 N is obtained at 600 rpm and 150 mm/min. The hardness of the joint presents a “W” morphology and the minimum hardness is obtained at the heat affected zone. The joints present tensile fracture and shear fracture when the advancing side and RS bare the main loads, respectively.

Performance Evaluation of Alternating Current Square Waveform Submerged Arc Welding as a Candidate for Fabrication of Thick Welds in 2.25Cr-1Mo Heat-Resistant Steel

AbstractThe paper evaluates the performance of alternating current (AC) square waveform submerged arc welding (SAW) as a candidate technology for manufacturing thick welds for high-pressure vessels. A new mathematical formulation for calculating melting efficiency in square waveform arc welding is presented. The melting efficiency and the heat consumption are presented as a mathematical model of welding parameters, namely welding current, welding speed, current frequency, and electrode negativity (EN) ratio. The proposed approach is demonstrated through the welding of 2.25Cr-1Mo heat-resistant steel performed over a wide range of welding parameters. The investigation provides deeper insights into the interplay between process parameter, total heat consumption, and melting efficiency. The effect on flux consumption is also explained. The melting efficiency is inversely proportional to flux consumption. The welding heat does not necessarily promote the plate melting. Improper use of welding heat may lead to decreased melting efficiency and increased unwanted melting and consumption of welding flux. Compared to the conventional direct current (DC) power sources, the AC square waveform welding achieves almost the same order of melting efficiency with added advantages of better weld bead shape and flux consumption in a desirable range. The two additional parameters (frequency and EN ratio) of the AC square waveform power source provide more freedom to fine-tune the process and thereby efficiently use welding heat. The results of this investigation will be advantageous to the designers and fabricators of high-pressure vessels using AC square waveform welding.

Cross-Wire Projection Welding of Aluminium Alloys in Relation to Pneumatic and Electromechanical Electrode Force Systems

The cross wire projection welding of wires (Al 5182, =4 mm) performed using the conventional (i.e. pneumatic) electrode force system was subjected to thorough numerical analysis. Calculations were performed until one of adopted boundary conditions, i.e. maximum welding time, maximum penetration of wires, the occurrence of expulsion or the exceeding of the temperature limit in the contact between the electrode and the welded material was obtained. It was observed that the ring weld was formed within the entire range of welding parameters. The process of welding was subjected to optimisation through the application of a new electromechanical electrode force system and the use of a special hybrid algorithm of electrode force and/or displacement control. Comparative numerical calculations were performed (using SORPAS software) for both electrode force systems. Technological welding tests were performed using inverter welding machines (1 kHz) provided with various electrode force systems. The research also involved the performance of metallographic and strength (peeling) tests as well as measurements of welding process characteristic parameters (welding current and voltage).The welding process optimisation involving the use of the electromechanical force system and the application of the hybrid algorithm of force control resulted in i) more favourable space distribution of welding power, ii) energy concentration in the central zone of the weld, iii) favourable (desired) melting of the material within the entire weld transcrystallisation zone and iv) obtainment of a full weld nugget.

Multi-variable statistical models for predicting bead geometry in gas metal arc welding

Statistical models were developed to study the effect of gas metal arc welding process parameters (i.e., wire feed speed, voltage, travel speed, and shielding gas chemistry) on the resultant weld bead width, penetration, and reinforcement height, using a factorial design of experiment. Analysis of variance (ANOVA) indicated that the weld width depended on voltage, travel speed, gas type, and the interactions between these factors. The weld penetration depended only on wire feed speed and gas type, as well as the two-way interactions of wire feed speed with travel speed and gas type. Reinforcement height depended on travel speed, wire feed speed, and their two-way interactions with gas type. Residual analysis revealed that all assumptions inherent in the regression analysis were satisfied over the range of welding parameters considered in this study. The predictive power of the statistical models was validated using intermediate process parameter values in the experimental design, and it was found that predicted values were mainly in agreement with the measured values for a 95% prediction interval.

A comparison study of BPN and SVM prediction models for inherent deformations of T-welded joints

The inherent deformation method has a significant advantage in predicting the welding deformations for large and complex welded structures, but the premise of applying this calculation method is to determine the values of inherent deformations in a given welded joint in advance. Therefore, it is a problem worthy of study to provide an accurate and rapid evaluation for the inherent deformations in a specific type of welded joint. In this study, an uncoupled thermo-elastic-plastic finite element (TEP FE) model was first developed to simulate the T-joint fillet welding process, and the welding experiments were performed to verify the accuracy of the developed TEP FE model. Then the numerical experiments were carried out to provide the informative data for the establishment of the BPN and SVM models. The appropriate network of the BPN model and the optimal parameters of the SVM model were obtained by the trial-and-error method and genetic algorithm (GA), respectively. In these two models, the input variables are the welding speed, current, voltage, and plate thickness, and the transverse and longitudinal inherent deformations are considered to be the output variables. The research results demonstrate that both the BPN model and SVM model can give a better prediction for the inherent deformations with acceptable accuracy. However, compared with the BPN model, the SVM model shows a better generalization ability for the data outside the training set and is more suitable for predicting the inherent deformations within a certain range of welding parameters.

Cross-wire projection welding of aluminium alloys\u2014pneumatic and electromechanical electrode force systems

The article discusses the optimisation of the conventional resistance welding process performed using the pneumatic (electrode) force system (PFS) by applying the electromechanical force system (EFS) and a new algorithm enabling the control of the force and/or displacement of welding machine electrodes, particularly during the flow of current. The research work described in the article aimed at the in-depth numerical analysis of the projection cross-wire welding of bars made of aluminium alloy Al 5182, having a diameter of 4 mm, in relation to two electrode force systems, i.e. the PFS and the EFS. The research-related tests involved experimental verification. In addition, the article presents advantages of the new control system. Calculations were performed until one of the adopted boundary conditions, i.e. the maximum welding time, the maximum penetration of wires (bars), the occurrence of expulsion or the exceeding of the temperature limit in the contact between the electrode and the welded material was obtained. For the PFS, it was observed that the ring weld was formed within the entire range of welding parameters. Numerical calculations were performed using SORPAS software. Technological welding tests were performed using inverter welding machines (1 kHz) provided with various electrode force systems. The research also involved the performance of metallographic and strength (peeling) tests as well as measurements of welding process characteristic parameters (welding current and voltage). The welding process optimisation involving the use of the EFS and the application of the hybrid algorithm of force control resulted in (i) more favourable space distribution of welding power, (ii) energy concentration in the central zone of the weld, (iii) favourable (desired) melting of the material within the entire weld transcrystallisation zone, (iv) obtainment of a full weld nugget and (v) over 20% longer weld nugget diameter.

Study on the Effect of Energy-Input on the Joint Mechanical Properties of Rotary Friction-Welding

The objective of the present study is to investigate the effect of energy-input on the mechanical properties of a 304 stainless-steel joint welded by continuous-drive rotary friction-welding (RFW). RFW experiments were conducted over a wide range of welding parameters (welding pressure: 25–200 MPa, rotation speed: 500–2300 rpm, welding time: 4–20 s, and forging pressure: 100–200 MPa). The results show that the energy-input has a significant effect on the tensile strength of RFW joints. With the increase of energy-input, the tensile strength rapidly increases until reaching the maximum value and then slightly decreases. An empirical model for energy-input was established based on RFW experiments that cover a wide range of welding parameters. The accuracy of the model was verified by extra RFW experiments. In addition, the model for optimal energy-input of different forging pressures was obtained. To verify the accuracy of the model, the optimal energy-input of a 170 MPa forging pressure was calculated. Three RFW experiments in which energy-input was equal to the calculated value were made. The joints’ tensile strength coefficients were 90%, 93%, and 96% respectively, which proved that the model is accurate.

Some effects of tool geometric features on friction stir weld response parameters

ABSTRACTPin geometries (shape, dimensions, and surface features) have significant effects on friction stir welding, dictating, to some extent, the material flow which in turn affects process variables and joint quality. In this paper, volumetric defect content and process response variables (in-plane forces, torque, power, and temperature) as a function of pin thread forms and features (thread/flat/flute) on mildly tapered conical pins were examined in AA6061-T6 for a range of welding parameters. The coarser thread pitch with different pin features performed better for producing good quality welds compared to finer threaded pins. Forge force requirements can be minimised using counter-flow flutes in threaded pin. Variations of nugget geometry, torque, power, and temperature were reported to correlate their dependence on pin features.

Influence of Shielding Gas Composition on Structure and Mechanical Properties of Wire and Arc Additive Manufactured Inconel 625

Wire and arc additive manufacturing (WAAM) is becoming an increasingly important process for manufacture of components with complex geometry, being used for products made for products made from expensive metals such as Inconel 625. The shielding gas used to protect the molten metal is one of the key process parameters due to its significant impact on the structure and mechanical properties of the final product. In this study, four samples were made using different shielding gas mixtures. Due to its high productivity, a metal active gas (MAG) welding process was used. Process stability and productivity rate were the main criteria used to determine the optimal range of welding parameters. Geometrical characteristics of the produced structures were analyzed. Finally, destructive tests were conducted on test specimens, and the data analyzed. The influence of the shielding gas composition on the structure and mechanical properties was determined, and conclusions are drawn.

Cross-Wire Projection Welding of Aluminium Alloys in Relation to Pneumatic and Electromechanical Electrode Force Systems

The cross wire projection welding of wires (Al 5182, =4 mm) performed using the conventional (i.e. pneumatic) electrode force system was subjected to thorough numerical analysis. Calculations were performed until one of adopted boundary conditions, i.e. maximum welding time, maximum penetration of wires, the occurrence of expulsion or the exceeding of the temperature limit in the contact between the electrode and the welded material was obtained. It was observed that the ring weld was formed within the entire range of welding parameters. The process of welding was subjected to optimisation through the application of a new electromechanical electrode force system and the use of a special hybrid algorithm of electrode force and/or displacement control. Comparative numerical calculations were performed (using SORPAS software) for both electrode force systems. Technological welding tests were performed using inverter welding machines (1 kHz) provided with various electrode force systems. The research also involved the performance of metallographic and strength (peeling) tests as well as measurements of welding process characteristic parameters (welding current and voltage).The welding process optimisation involving the use of the electromechanical force system and the application of the hybrid algorithm of force control resulted in i) more favourable space distribution of welding power, ii) energy concentration in the central zone of the weld, iii) favourable (desired) melting of the material within the entire weld transcrystallisation zone and iv) obtainment of a full weld nugget.