scholarly journals Automatic Control of the Weld Bead Geometry

2020 ◽  
Author(s):  
Guillermo Alvarez Bestard ◽  
Sadek Crisostomo Absi Alfaro
Keyword(s):  
Automatic Control ◽  
Dynamic Models ◽  
Welding Process ◽  
Industrial Applications ◽  
Weld Bead ◽  
Bead Geometry ◽  
Single Input Single Output ◽  
Control Loops ◽  
Orbital Welding ◽  
Estimation And Control

Automatic control of the welding process is complex due to its nonlinear and stochastic behavior and the difficulty for measuring the principal magnitudes and closing the control loop. Fusion welds involve melting and subsequent solidification of one or more materials. The geometry of the weld bead is a good indicator of the melting and solidification process, so its control is essential to obtain quality junctions. Different sensing, modeling, estimation, and control techniques are used to overcome this challenge, but most of the studies are using static single-input/single-output models of the process and focusing on the flat welding position. However, theory and practice demonstrate that dynamic models are the best representation to obtain satisfactory control performance, and multivariable techniques reduce the effect of interactions between control loops in the process. Also, many industrial applications need to control orbital welding. In this chapter, the above topics are discussed.

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.

A Study of Software Approach for Predicting Weld Bead Geometry in Shielded Metal Arc Welding (SMAW) Process

2014 ◽  
Vol 554 ◽  
pp. 386-390
Author(s):  
C.W. Mohd Noor ◽  
Manuhutu Ferry ◽  
W.B. Wan Nik
Keyword(s):  
Arc Welding ◽  
Welding Process ◽  
Weld Bead ◽  
Bead Geometry ◽  
Shielded Metal Arc Welding ◽  
Depth Of Penetration ◽  
Weld Bead Geometry ◽  
Bead Width ◽  
Real Process ◽  
Metal Arc Welding

The prediction of the optimal weld bead width is an important aspect in shielded metal arc welding (SMAW) process as it is related to the strength of the weld. This paper focuses on investigation of the development of the simple and accurate model for prediction of weld bead geometry. The experiment used welding current, arc length, welding speed, welding gap and electrode diameter as input parameters. While output parameters are bead width, depth of penetration and weld reinforcement. A number of 33 mild steel plate specimens had undergone the SMAW welding process. The experimental data was used to develop mathematical models using SPSS software. The actual and predicted values of the weld bead geometry are compared. The proposed models shows positive correlation to the real process.

Analysis of Weld Bead Parameters of Overlay Deposited on D2 Steel Components by Plasma Transferred Arc (PTA) Process

2013 ◽  
Vol 755 ◽  
pp. 39-45 ◽  
Author(s):  
F. García-Vázquez ◽  
A. Aguirre ◽  
Ana Arizmendi-Morquecho ◽  
H.M. Hernández-García ◽  
L. Santiago-Bautista ◽  
...  
Keyword(s):  
Tool Steel ◽  
Cold Work ◽  
Welding Process ◽  
Wear Test ◽  
Weld Bead ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Plasma Transferred Arc ◽  
Transferred Arc ◽  
D2 Steel

Plasma Transferred Arc (PTA) process is increasingly used in applications where enhancement of wear, corrosion and heat resistance of metals surface is required. The shape of weld bead geometry affected by the PTA welding process parameters is an indication of the quality of the weld. PTA is a versatile method of depositing high-quality metallurgically fused deposits on relatively low cost surfaces. The overlay deposited is an alloy that is hard and more corrosion resistant than counterparts laid down by Gas Tungsten Arc Welding (GTAW) or Oxy Fuel Welding (OFW) processes. Weld deposits are characterized by very low levels of inclusions, oxides, and discontinuities. This process produces smooth deposits that significantly reduce the amount of post weld machining required. Metal-Mechanic industry continuously requires recovering tool steel components subjected to severe wear. The steel known as D2 is considered to be a high carbon, high chromium cold work tool steel. In this research, weld beads were deposited on D2 steel by using PTA process with different parameters as welding current and travel speed using base nickel filler metal. In order to evaluate the metallurgical features on the weld beads/substrate interface a microstructural characterization was performed by using Scanning Electron Microscopy (SEM) and to evaluate the mechanical properties was conducted the wear test.

Using Artificial Neural Networks to Predict the Effect of Input Parameters on Weld Bead Geometry for SAW Process

2021 ◽  
Vol 54 (2) ◽  
pp. 309-315
Author(s):  
Majid Midhat Saeed ◽  
Ziad Shakeeb Al Sarraf
Keyword(s):  
Neural Network ◽  
Arc Welding ◽  
Welding Process ◽  
Submerged Arc Welding ◽  
Weld Bead ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
The Neural Network ◽  
Input Parameters ◽  
Submerged Arc

Based on high quality and reliability, one of the most efficient methods for joining metals is Submerged Arc Welding (SAW). In this presented work, an attempt has been successfully taken to develop a model to predict the effect of input parameters on weld bead geometry of submerged arc welding process with the help of neural network technique and analysis of various process control variables and important of weld bead parameters in submerged arc welding. The complexity non-linear relationships of input / output variables for any computational models can be addressed by using artificial neural networks (ANN). Today, ANN represents a powerful modeling technique, that depend on statistical approach, presently practiced in many fields of engineering for modeling complex relationships that other physical models cannot be explained it easily. A welding process with automatic or semiautomatic is required to complete the weld through using tubular electrode with consumable flux. Parameters such as welding current, welding speed and voltage are influenced on the quality of the joints. The work conducts many experiments; these are basically depending on many factors and levels. A selection of 2205 duplex stainless steel is carried out in this study to conduct three factors and five levels of central composite design. Neural network model structure having number of neurons layers such as (3 input layers, 1 hidden layer and 3 output layers) with back propagation algorithm has been successfully applied to extract weld bead geometry from predicting the effect of input parameters. Good agreement was obtained between predicted and experiment results, however process parameters such as speed shows opposite effect on all weld parameters. It was seen that weld height and width are proportional to the amount of input current. The prediction of the neural network model showed excellent agreement with the actual results, which indicate that the neural network is viable means for predicting of not only weld bead geometry, but also other parameters such as polarity, current type and flux geometry. This recommends setting the neural network to be applicable for real time work.

Performance of weld bead profile during A-TIG welding on nitrogen alloyed stainless steel

2021 ◽  
Author(s):  
Akash Deep ◽  
Vivek Singh ◽  
Som Ashutosh ◽  
M. Chandrasekaran ◽  
Dixit Patel
Keyword(s):  
Stainless Steel ◽  
Welding Process ◽  
Weld Bead ◽  
Tig Welding ◽  
Inert Gas ◽  
Bead Geometry ◽  
Depth Of Penetration ◽  
Weld Bead Geometry ◽  
A Tig Welding ◽  
Arc Welding Process

Abstract Austenitic stainless steel (ASS) is widely fabricated by tungsten inert gas (TIG) welding for aesthetic look and superior mechanical properties while compared to other arc welding process. Hitherto, the limitation of this process is low depth of penetration and less productivity. To overcome this problem activated tungsten inert gas (A-TIG) welding process is employed as an alternative. In this investigation the welding performance of conventional TIG welding is compared with A-TIG process using TiO2 and SiO2 flux with respect to weld bead geometry. The experimental investigation on A-TIG welding of ASS-201 grade shows TiO2 flux helps in achieve higher penetration as compared to SiO2 flux. While welding with SiO2 the hardness in HAZ and weld region higher than that of TIG welding process.

scholarly journals Modeling and Optimization of Weld Bead Profile with Varied Welding Stages for Weathering Steel A606

2021 ◽  
Author(s):  
Dawei Zhao ◽  
Yuriy Bezgans ◽  
Nikita Vdonin ◽  
Liudmila Radionova ◽  
Vitaly Bykov
Keyword(s):  
Desirability Function ◽  
Research Work ◽  
Welding Process ◽  
Weld Bead ◽  
Welding Parameters ◽  
Weathering Steel ◽  
Bead Geometry ◽  
Feed Speed ◽  
Geometric Features ◽  
Weld Bead Geometry

Abstract The profile of the welding bead changes with the welding process parameters during the gas metal arc welding (GMAW) process, the reinforcement disappears and the penetration becomes sunken when the excessive welding heat input is applied. However, little research work is specially planned to cope with the studying of welding bead at these stages. A systematic studying of the relationships among the welding process variables and welding bead geometric features and optimization of the welding quality is presented. The influences of the welding technological parameters (voltage, welding speed, and wire feed speed) on the welding geometry were revealed and the models correlating them were established. The features of the weld bead geometry were composed of top reinforcement width, top reinforcement height, penetration depth, bottom reinforcement width, and bottom reinforcement height. By the desirability function approach, the recommendation of suitable welding parameters to meet the contradicting demands of multiple bead geometric features is fulfilled. The microstructure in different welding regions and mechanical performances of the welding joints produced by the verification test were also studied.

scholarly journals Representation of gas metal arc pulsed welding process behavior on bead geometry: a study of leading variables

2021 ◽  
Vol 2139 (1) ◽  
pp. 012008
Author(s):  
J L Lázaro Plata ◽  
C S Sánchez Rincón
Keyword(s):  
Welding Process ◽  
Weld Bead ◽  
Structural Quality ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Automatic Welding ◽  
Cored Wire ◽  
Experimental Development ◽  
Welding Processes

Abstract Gas metal arc welding is one of the most influential processes in the production and repair of structures and equipment; therefore, the need to improve the productivity and quality of welded joints has led to the development of techniques for good control of welding parameters. Also, the development of semi-automatic welding processes led to the control of one of the variables such as pulsed current; this technique is characterized by a lower heat input and lower energy expenditure, which directly influences the structural quality of the welded joint and the geometry of the weld bead. This work focused on evaluating the effects of various welding operating parameters using the central composite design tool based on the response surface methodology; next, the experimental development employed an inverter type power source for weld depositions, a commercial grade Stargold clean 96% Ar and 4% CO2 shielding gas at the rate of 15 L/min stationary arc, a 1.2 mm metal cored wire for welding deposit and a carbon steel base plate with a thickness of 6 mm. During the welding process, the torch was kept at a 90° inclination and a 16 mm stroke. To examine the adequacy of the empirical models and the significance of the regression coefficients, the variance analysis was employed. Consequently, the graphs were obtained through the determination of the model; from the statistical results obtained, it was shown that the above models were adequate to predict the weld width, bead height, and penetration within the range of variables studied. Furthermore, it was observed that the wire feed rate it has a very marked effect on weld bead geometry, followed by frequency pulse and peak current; finally, the effectiveness of employing these methodologies for the management of variables attributing to the execution of welding tasks with higher accuracy was demonstrated.

Parametric Optimization of TIG Welding on 316L Austenitic Stainless Steel by Grey-Based Taguchi Method

2011 ◽  
Vol 383-390 ◽  
pp. 4667-4671 ◽  
Author(s):  
Nanda Naik Korra ◽  
K.R. Balasubramanian
Keyword(s):  
Stainless Steel ◽  
Austenitic Stainless Steel ◽  
Gas Flow ◽  
Welding Process ◽  
Weld Bead ◽  
Bead Geometry ◽  
Depth Of Penetration ◽  
Weld Bead Geometry ◽  
Bead Width ◽  
Input Parameters

Gas Tungsten Arc Welding (GTAW) is one of the most widely used welding process in industry. The input parameters play a very significant role in determining the quality of a welded joint (geometry of weld bead). The joint quality can be evaluated by studying the features of weld bead geometry (output parameters) such as Bead Width (BW), Bead Height (BH) and Depth of Penetration (DP). Present study focused on welding of austenitic stainless steel sheets using GTAW process with 316L material. The output variables are determined according to gas flow rate, travel speed and current. Grey relational analysis is applied to optimize the input parameters simultaneously considering the multiple output variables. Finally, confirmation experiment has been conducted to validate the optimized parameters and found to be correlated.

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