Prediction of Flux Cored Arc Welding (FCAW) Parameters and Bead Geometry in Downhill Position (3F)

2014 ◽  
Vol 660 ◽  
pp. 342-346
Author(s):  
Nik Mohd Baihaki Abd Rahman ◽  
Abdul Ghalib Tham ◽  
Sunhaji Kiyai Abas ◽  
Razali Hassan ◽  
Yupiter H.P. Manurung ◽  
...  
Keyword(s):  
Arc Welding ◽  
Weld Bead ◽  
Welding Parameter ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Absolute Deviation ◽  
High Productivity ◽  
Flux Cored Arc Welding ◽  
Wide Range

The robot can perform Flux Cored Arc Welding (FCAW) at high productivity and consistency in quality. The quality of the welding depend on the selection of welding parameter and deposition geometry. These input has to be known before the start of production, generally the welding operator will obtain the information through experimental trial and error. This project planned to develop a tool that can advise the choice of welding parameter that produce quality weld bead with desired geometry. This research focused on the correlation of heat input on weld bead geometry and the range of welding parameter for fillet design welded in downhill direction (3F). From the correlation trend-line equations and welding parameter population boundary, the weld bead geometry and welding parameter for quality deposit are predicted. Consequently two calculators were developed to display the values digitally. The deviation of predicted bead geometry from actual welding is less than 1mm. Mean Absolute Deviation (MAD) is less than 0.4mm, accuracy is good. A wide range of welding parameters can be generated for quality welding at desired bead geometry.

Prediction of Welding Parameters and Weld Bead Geometry for GMAW Process in Overhead T-Fillet Welding Position (4F)

2013 ◽  
Vol 686 ◽  
pp. 320-324
Author(s):  
Mohamad Yazman Yaakub ◽  
Ghalib Tham ◽  
Wan Muhamad Amirun Wan Abd Rahim ◽  
Muhammad Amir Rusydi Mohd Radzi ◽  
Azhar Mahmud
Keyword(s):  
Steel Structures ◽  
Weld Bead ◽  
Welding Parameter ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Absolute Deviation ◽  
Fillet Welding ◽  
Mathematical Formulas ◽  
Welding Position

The prediction of welding parameters and weld bead geometry for GMAW process in Overhead T-fillet welding position (4F) is presented in this paper. This welding position is applied in construction of steel structures and ship building. The task to discover the range of welding parameter that can deposit quality fillet weld in overhead position is difficult, and the cost of developing them by trial and error is high. Robotic GMAW welder is employed to weld in 4F position with CO2 shielding. The current, voltage and speed as parameters, wire extension at 13mm constant. Only weld coupons are analyzed by macro-etching and the fillet geometry is plotted graphically to display the correlation with the respective welding parameter, particularly the heat input. Trend-lines with mathematical formulas are selected to develop the fillet geometry predictor. The predicted fillet geometry is validated by comparing with the values from actual welded coupons. The mean absolute deviation (MAD) of the predicting calculator is less than 1.0mm, it is therefore accurate and valid for industrial application.

Correlation between Welding Parameter and Bead Geometry of Flux Cored Arc Welding (FCAW) in Horizontal Position (2F)

2014 ◽  
Vol 564 ◽  
pp. 549-554
Author(s):  
Nik Mohd Baihaki Abd Rahman ◽  
Abdul Ghalib Tham ◽  
Sunhaji Kiyai Abas ◽  
Razali Hassan ◽  
Yupiter H.P. Manurung ◽  
...  
Keyword(s):  
Heat Input ◽  
Arc Welding ◽  
Weld Bead ◽  
Welding Parameter ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Automatic Welding ◽  
Trend Line ◽  
Flux Cored Arc Welding ◽  
Good Prediction Accuracy

A robotic system can convert the semi-automatic Flux Cored Arc Welding (FCAW) to an automatic welding system. The critical requirement in automated welding process is that the optimal welding parameter has to be set before welding start. These input welding parameters cannot be easily guessed unless one has the knowledge. Only very specific range of heat input that produces quality weld deposition. The correlation between the heat input and fillet weld bead can be displayed in a unique trend-line graph. Mathematical formulas that match the trend-line profile can be used to create a prediction calculator that displays the digital values of weld bead geometry when welded at a specific range of heat input. Small Mean Absolute Deviation between predicted and measured geometry means good prediction accuracy. With this correlation chart, the welding parameter for quality weld bead can be selected and the geometry of FCAW weld deposition in 2F position can be predicted accurately without trial and error.

Predicting Bead Geometry of 2F-Fillet Joint Welded by Small Wire SAW

2012 ◽  
Vol 576 ◽  
pp. 185-188 ◽  
Author(s):  
Shahfuan Hanif Ahmad Hamidi ◽  
Abdul Ghalib Tham ◽  
Yupiter H.P. Manurung ◽  
Sunhaji Kiyai Abas
Keyword(s):  
Welding Current ◽  
Weld Bead ◽  
Welding Parameter ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Absolute Deviation ◽  
Fillet Weld ◽  
Welding Condition ◽  
Code Of Practice ◽  
The Cost

The cost of development of WPS will be very expensive if the welding parameter is selected based on trial and error. Optimal welding condition cannot be easily guessed unless the operator has records of good welding. If a calculator that can predict the welding parameter for the desired bead geometry accurately, such tool will be extremely useful for any fabrication industry. This paper intends to investigate the correlation between the welding parameter and weld bead geometry of 2F position T-fillet carbon steel, when welded by 1.2 mm diameter wire submerged arc welding. Keeping only one parameter as variable, 2F fillet weld coupons are welded by SAW with a range of welding current, welding voltage and welding speed. Only weld bead geometry that complied with the quality requirement of code of practice AWS D1.1 is considered. The trendline graph is created to fit the correlation between the heat input and the fillet weld geometry. By incorporating the trendline formulas into the calculator, the weld bead geometry can be predicted accurately for any welding parameter. The mean absolute deviation (MAD) between the predicted geometry and the experimental results is less than 0.50mm.

Analysis of flux cored arc welding process parameters by hybrid taguchi approach

2014 ◽  
Vol 11 (6) ◽  
pp. 575-588
Author(s):  
P. Sreeraj ◽  
T. Kannan ◽  
Maji Subhasis
Keyword(s):  
Taguchi Method ◽  
Process Parameters ◽  
Arc Welding ◽  
Welding Process ◽  
Optimization Techniques ◽  
Weld Bead ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Flux Cored Arc Welding ◽  
Two Hybrid

This paper presents calculation of the welding process parameters for obtaining optimal weld bead geometry in Flux Cored arc welding (FCAW) process. Bead on plate welding was carried as per L16 orthogonal array. In this paper weld bead geometry such as penetration, bead width, reinforcement and percentage of dilution of IS 2062 structural steel plates investigated. Two hybrid techniques firstly Taguchi method coupled with Grey relational analysis and secondly Taguchi method in combination with desirability function (DF) approach has been applied in this paper. Comparison made between two hybrid optimization techniques are made to analyze to choose the best method. Optimal results have been confirmed by confirmatory experiment which showed satisfactory results.

Mathematical Expression for the Prediction of Penetration in Butt Joints for Duplex Stainless Steel SAF-2205

2003 ◽  
Author(s):  
Mari´a Carolina Payares ◽  
Minerva Dorta Almenara
Keyword(s):  
Stainless Steel ◽  
Arc Welding ◽  
Welding Process ◽  
Weld Bead ◽  
Welding Parameters ◽  
Linear Regression Method ◽  
Bead Geometry ◽  
Butt Joints ◽  
Weld Bead Geometry ◽  
Saf 2205

In order to understand the mechanism of weld bead formation, a relationship between arc welding parameters and weld bead geometry must be established. This relationship is also necessary to forecast penetration variables allowing to optimize welding parameters for particular applications. Specifically in duplex stainles steel SAF-2205 welding, the influence of arc current, arc voltage and welding speed on the penetration have been empirically studied. In this research, using a multiple linear regression method, the statistical analyses produced twelve (12) potential function dependent of these welding parameters that determines the weld bead geometry in butt joints of DSS SAF 2205 using GAs Metal Arc Welding process. the mathematical model gave as a result, a very approximate contour of the weld bead geometry between the established ranges of welding parameters used. Also, the influence of these variables on the weld panetration is studied, providing with new evidence in stainless steel welding.

A modified version of MATLAB application window for predicting the weld bead profile and stress–strain plot of AA5052 CMT weldment using ER4043

SIMULATION ◽  
2021 ◽  
pp. 003754972110315
Author(s):  
B Girinath ◽  
N Siva Shanmugam
Keyword(s):  
Strain Curve ◽  
Weld Bead ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Hybrid Technique ◽  
Stress Strain Curve ◽  
Stress Strain ◽  
Weld Bead Geometry ◽  
Inference System ◽  
Engineering Stress

The present study deals with the extended version of our previous research work. In this article, for predicting the entire weld bead geometry and engineering stress–strain curve of the cold metal transfer (CMT) weldment, a MATLAB based application window (second version) is developed with certain modifications. In the first version, for predicting the entire weld bead geometry, apart from weld bead characteristics, x and y coordinates (24 from each) of the extracted points are considered. Finally, in the first version, 53 output values (five for weld bead characteristics and 48 for x and y coordinates) are predicted using both multiple regression analysis (MRA) and adaptive neuro fuzzy inference system (ANFIS) technique to get an idea related to the complete weld bead geometry without performing the actual welding process. The obtained weld bead shapes using both the techniques are compared with the experimentally obtained bead shapes. Based on the results obtained from the first version and the knowledge acquired from literature, the complete shape of weld bead obtained using ANFIS is in good agreement with the experimentally obtained weld bead shape. This motivated us to adopt a hybrid technique known as ANFIS (combined artificial neural network and fuzzy features) alone in this paper for predicting the weld bead shape and engineering stress–strain curve of the welded joint. In the present study, an attempt is made to evaluate the accuracy of the prediction when the number of trials is reduced to half and increasing the number of data points from the macrograph to twice. Complete weld bead geometry and the engineering stress–strain curves were predicted against the input welding parameters (welding current and welding speed), fed by the user in the MATLAB application window. Finally, the entire weld bead geometries were predicted by both the first and the second version are compared and validated with the experimentally obtained weld bead shapes. The similar procedure was followed for predicting the engineering stress–strain curve to compare with experimental outcomes.

scholarly journals Experimental and Numerical Analysis on TIG Arc Welding of Stainless Steel Using RSM Approach

Metals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1659
Author(s):  
Sasan Sattarpanah Karganroudi ◽  
Mahmoud Moradi ◽  
Milad Aghaee Attar ◽  
Seyed Alireza Rasouli ◽  
Majid Ghoreishi ◽  
...  
Keyword(s):  
Heat Flux ◽  
Stainless Steel ◽  
Welding Speed ◽  
Arc Welding ◽  
Welding Process ◽  
Weld Bead ◽  
Bead Geometry ◽  
Depth Of Penetration ◽  
Weld Bead Geometry ◽  
Bead Width

This study involves the validating of thermal analysis during TIG Arc welding of 1.4418 steel using finite element analyses (FEA) with experimental approaches. 3D heat transfer simulation of 1.4418 stainless steel TIG arc welding is implemented using ABAQUS software (6.14, ABAQUS Inc., Johnston, RI, USA), based on non-uniform Goldak’s Gaussian heat flux distribution, using additional DFLUX subroutine written in the FORTRAN (Formula Translation). The influences of the arc current and welding speed on the heat flux density, weld bead geometry, and temperature distribution at the transverse direction are analyzed by response surface methodology (RSM). Validating numerical simulation with experimental dimensions of weld bead geometry consists of width and depth of penetration with an average of 10% deviation has been performed. Results reveal that the suggested numerical model would be appropriate for the TIG arc welding process. According to the results, as the welding speed increases, the residence time of arc shortens correspondingly, bead width and depth of penetration decrease subsequently, whilst simultaneously, the current has the reverse effect. Finally, multi-objective optimization of the process is applied by Derringer’s desirability technique to achieve the proper weld. The optimum condition is obtained with 2.7 mm/s scanning speed and 120 A current to achieve full penetration weld with minimum fusion zone (FZ) and heat-affected zone (HAZ) width.

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