Experimental Investigation on Laser Transmission Welding of Polycarbonate and Acrylic

2021 ◽  
pp. 160-180
Author(s):  
Dhiraj Kumar ◽  
Sudipta Paitandi ◽  
Arunanshu Shekhar Kuar ◽  
Dipankar Bose
Keyword(s):  
Mathematical Model ◽  
Process Parameters ◽  
Welding Speed ◽  
Laser Power ◽  
Optimum Parameter ◽  
Optimization Technique ◽  
Welding Process ◽  
Parameter Setting ◽  
Laser Transmission Welding ◽  
Weld Width

This chapter presents the effect of various process parameters, namely laser power, pulse frequency, and welding speed, on the weld shear strength and weld width using a diode laser system. Here, laser transmission welding of transparent polycarbonate and black carbon filled acrylic each of 2.8 mm thickness have been performed to create lap joint by using low power laser. Response surface methodology is applied to develop the mathematical model between the laser welding process parameters and the responses of weld joint. The developed mathematical model is tested for its adequacy using analysis of variance and other adequacy measures. It has been observed that laser power and welding speed are the dominant factor followed by frequency. A confirmation test has also been conducted to validate the experimental results at optimum parameter setting. Results show that weld strength of 34.3173 N/mm and weld width of 2.61547 mm have been achieved at optimum parameter setting using desirability function-based optimization technique.

scholarly journals Study on Effect of Laser Process Parameters on Laser Transmission Weld Parameters using ANSYS

2021 ◽  
Vol 23 (07) ◽  
pp. 1050-1057
Author(s):  
Girish Kumar R ◽  
◽  
Abhay Agarwal ◽  
Utkarsha Mohan ◽  
Shounak Dey ◽  
...  
Keyword(s):  
Process Parameters ◽  
Welding Speed ◽  
Laser Power ◽  
Element Model ◽  
Weld Interface ◽  
Negative Influence ◽  
Maximum Temperature ◽  
Laser Transmission Welding ◽  
Weld Width ◽  
Weld Parameters

In recent years, a mode of welding that has garnered a considerable amount of interest is the laser transmission welding of thermoplastics. Laser transmission welding is now being used as an alternative to adhesives to join two thermoplastics. In this study, a finite element model has been developed to simulate the laser transmission welding of polypropylene. The movement of the laser beam was done using a Moving Heat Source in Ansys®. Process parameters namely laser power, welding speed, and the number of passes have been studied in order to investigate their effects on the temperatures and the weld widths achieved during welding. It was found that an increase in the laser power had a positive effect on the maximum temperature at the weld interface as well as the weld width. Similarly, an increase in the welding speed had a negative influence on the maximum temperature at the weld interface as well as the weld width.

Modeling of Weld Lap-Shear Strength for Laser Transmission Welding of Thermoplastic Using Artificial Neural Network

2012 ◽  
Vol 445 ◽  
pp. 454-459 ◽  
Author(s):  
M.R. Nakhaei ◽  
N.B. Mostafa Arab ◽  
F. Kordestani
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Shear Strength ◽  
Laser Welding ◽  
Process Parameters ◽  
Welding Speed ◽  
Laser Power ◽  
Laser Transmission Welding ◽  
Lap Shear Strength ◽  
Lap Shear

Laser welding of plastic materials has a wide range of applications in the packaging, medical, electronics and automobile industries provided it can predict high quality welds compared with other joining methods. Laser welding process parameters can affect the quality of welds. In this paper, Artificial Neural Network (ANN) is used to model the effects of laser power, welding speed, clamp pressure and stand-off distance on weld lap-shear strength in laser transmission welding (LTW) of acrylic (polymathy methacrylate). A set of experimental data on diode laser weld lap-shear strengths was used to train and test the ANN from which the neurons relations were gradually extracted to develop a model. The developed ANN model can be used for the analysis and prediction of the complex relationships between the above mentioned process parameters and weld lap-shear strength. The results indicated that increase in laser power and clamp pressure increases the weld lap-shear strength whereas welding speed and stand off distance had a decreasing affect on shear strength at high value.

scholarly journals Welding Process Optimization of WELDOX960 High Strength Steel

2018 ◽  
Vol 207 ◽  
pp. 04005
Author(s):  
Min Hu
Keyword(s):  
Penetration Depth ◽  
Process Optimization ◽  
Process Parameters ◽  
Welding Speed ◽  
High Strength Steel ◽  
Welding Process ◽  
Welding Current ◽  
High Strength ◽  
Influence Of Process Parameters ◽  
Steel Analysis

This paper studies WELDOX960 high strength steel, analysis of the welding ability of WELDOX960 high strength steel. Analyze the weld ability of WELDOX960 high-strength steel materials, and study the influence of process parameters such as welding current, welding voltage, and welding speed on penetration depth and weld width in the automated welding process. Through this test, the welding process is optimized to ensure the weld quality. The results show that WELDOX960 high-strength steel adopts multi-layer and multi-pass welding to form better welds.

scholarly journals Optimization of FCAW Parameters for Ferrite Content in 2205 DSS Welds Based on the Taguchi Design Method

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Tianqi Li ◽  
Yingying Zhang ◽  
Lei Gao ◽  
Yunhao Zhang
Keyword(s):  
Mathematical Model ◽  
Process Parameters ◽  
Welding Speed ◽  
Design Method ◽  
Welding Current ◽  
Taguchi Design ◽  
Experimental Results ◽  
Ferrite Content ◽  
Welding Parameters ◽  
Torch Angle

This study presents the Taguchi design method with L9 orthogonal array which was carried out to optimize the flux-cored arc welding (FCAW) process parameters such as welding current, welding voltage, welding speed, and torch angle with reference to vertical for the ferrite content of duplex stainless steel (DSS, UNS S32205) welds. The analysis of variance (ANOVA) was applied, and a mathematical model was developed to predict the effect of process parameters on the responses. The results indicate that welding current, welding voltage, welding speed, torch angle with reference to vertical, and the interaction of welding voltage and welding speed are the significant model terms connected with the ferrite content. The ferrite content increases with the increase of welding speed and torch angle with reference to vertical, but decreases with the increase of welding current and welding voltage. Through the developed mathematical model, the target of 50% ferrite content in weld metal can be obtained when all the welding parameters are set at the optimum values. Finally, in order to validate experimental results, confirmation tests were implemented at optimum working conditions. Under these conditions, there was good accordance between the predicted and the experimental results for the ferrite content.

Laser Transmission Welding of Thermoplastics—Part II: Experimental Model Validation

2007 ◽  
Vol 129 (5) ◽  
pp. 859-867 ◽  
Author(s):  
James D. Van de Ven ◽  
Arthur G. Erdman
Keyword(s):  
Polyvinyl Chloride ◽  
Welding Process ◽  
Weld Strength ◽  
Average Error ◽  
Welding Parameters ◽  
Laser Transmission Welding ◽  
Weld Width ◽  
Additional Information ◽  
Primary Model ◽  
Clamping Pressure

Two laser transmission welding experiments involving polyvinyl chloride are presented that aim to validate a previously presented welding model while helping to further understand the relationship between welding parameters and weld quality. While numerous previous research papers have presented the results of laser welding experiments, there exists minimal work validating models of the welding process. The first experiment explores the interaction of laser power and welding velocity while the second experiment explores the influence of clamping pressure. Using the weld width as the primary model output, the agreement between the welding experiments and the model have an average error of 5.6%. This finding strongly supports the validity of the model presented in Part I of this two paper set (Van de Ven and Erdman, 2007, ASME J. Manuf. Sci. Eng., 129, pp. 849–858). Additional information was gained regarding the operating window for laser transmission welding and the thermal decomposition of polyvinyl chloride. Clamping pressure was found to provide a small, but not statistically significant, influence on the visual appearance, weld width, and weld strength.

scholarly journals A Novel Method of Defect Detection Based on Experimental Investigation of Galvanized Steel Welded Plates Using Wobble Laser Process

2021 ◽  
Author(s):  
Sasan Sattarpanah Karganroudi ◽  
Ahmad Aminzadeh ◽  
Vincent Blériot Feujofack Kemda ◽  
Noureddine Barka
Keyword(s):  
Process Parameters ◽  
Predictive Models ◽  
Welding Process ◽  
Galvanized Steel ◽  
Welding Parameters ◽  
Indentation Hardness ◽  
Hardness Profile ◽  
Weld Width ◽  
Welding Defects ◽  
Geometrical Defects

Abstract This paper aims at investigating the effect of laser welding parameters on the hardness profile, using hardness mapping analyses, and welding geometry of galvanized steel plates. Hardness distribution and geometry deflection of galvanized welded thin plates are commonly applied in fields where the weld quality is of utmost importance. Due to the welding process and material condition, welding galvanized steel is one of the problematic matters in welding technology. Here, the design of experiment (DOE) approach is used to study the effect of process parameters. Using a pattern matrix of micro-indentation hardness experiment, the welding defects are visualized on hardness profile of the weld cross-section. The effect of process parameters on welding defect formation is then qualitatively analyzed. The geometrical defects of welding such as weld width and voids are then quantitatively studied based on analysis of variance (ANOVA), and predictive models of welding voids and weld seam width are developed based on the regression method. Response surface method (RSM) is then applied to define the trend of process factors interaction on the welding defects. The experimental results confirm the reliability of developed predictive models of welding defects geometry, weld width, and voids area of laser-welded galvanized plates.

scholarly journals Multi-Objective Optimization of MIG Welding and Preheat Parameters for 6061-T6 Al Alloy T-Joints Using Artificial Neural Networks Based on FEM

Coatings ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 998
Author(s):  
Qing Shao ◽  
Fuxing Tan ◽  
Kai Li ◽  
Tatsuo Yoshino ◽  
Guikai Guo
Keyword(s):  
Process Parameters ◽  
Welding Speed ◽  
Heat Input ◽  
Pareto Front ◽  
Welding Process ◽  
Residual Deformation ◽  
Welding Deformation ◽  
Mig Welding ◽  
Preheat Temperature ◽  
Multi Objective

To control the welding residual stress and deformation of metal inert gas (MIG) welding, the influence of welding process parameters and preheat parameters (welding speed, heat input, preheat temperature, and preheat area) is discussed, and a prediction model is established to select the optimal combination of process parameters. Thermomechanical numerical analysis was performed to obtain the residual welding deformation and stress according to a 100 × 150 × 50 × 4 mm aluminum alloy 6061-T6 T-joint. Owing to the complexity of the welding process, an optimal Latin hypercube sampling (OLHS) method was adopted for sampling with uniformity and stratification. Analysis of variance (ANOVA) was used to find the influence degree of welding speed (7.5–9 mm/s), heat input (1500–1700 W), preheat temperature (80–125 °C), and preheat area (12–36 mm). The range of research parameters are according to the material, welding method, thickness of the welding plate, and welding procedure specification. Artificial neural network (ANN) and multi-objective particle swarm optimization (MOPSO) was combined to find the effective parameters to minimize welding deformation and stress. The results showed that preheat temperature and welding speed had the greatest effect on the minimization of welding residual deformation and stress, followed by the preheat area, respectively. The Pareto front was obtained by using the MOPSO algorithm with ε-dominance. The welding residual deformation and stress are the minimum at the same time, when the welding parameters are selected as preheating temperature 85 °C and preheating area 12 mm, welding speed is 8.8 mm/s and heat input is 1535 W, respectively. The optimization results were validated by the finite element (FE) method. The error between the FE results and the Pareto optimal compromise solutions is less than 12.5%. The optimum solutions in the Pareto front can be chosen by designers according to actual demand.

scholarly journals The Effects of Different Gaps on the Weld Morphology, Microstructure and Residual Stress of AH36 Steel were Studied by Laser Arc Hybrid Welding

2022 ◽  
Vol 2160 (1) ◽  
pp. 012039
Author(s):  
Xiaoqi Hou ◽  
Xin Ye ◽  
Xiaoyan Qian ◽  
Haohao Jing ◽  
Peilei Zhang ◽  
...  
Keyword(s):  
Residual Stress ◽  
Process Parameters ◽  
Heat Affected Zone ◽  
Laser Power ◽  
Welding Process ◽  
Lower Surface ◽  
Thick Sheet ◽  
Hybrid Welding ◽  
Upper Bainite ◽  
Better Than

Abstract In this study, laser (TruDisk16002)-arc (MAG) hybrid welding was used to weld a 5mm thick sheet of AH36 steel with a gap of 0mm and 1mm. The results show that when the current of MAG is 205A, the voltage is 31.9V, and the laser power is 7.5KW, the welds of 0mm gap and 1mm gap are well formed, showing a typical nail shape, and the 0mm gap weld is better than 1mm. Under the same welding process parameters, the heat-affected zone of a 0mm gap weld is less than 1mm. Upper bainite is found in the 1mm weld gap structure. In the two gap cases, the residual stress on the lower surface is larger than that on the upper surface, and the residual stress in the 1mm weld gap is larger. The weldability of 0mm weld gap is better than 1mm.

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