On-Line Empirical Models for Control of Bead Geometry in Robotic Arc Welding Process

2011 ◽  
Vol 264-265 ◽  
pp. 367-372
Author(s):  
Joon Sik Son ◽  
Il Soo Kim ◽  
H.H. Kim ◽  
H.H. Na ◽  
J.H. Lee
Keyword(s):  
Gas Flow ◽  
Welding Process ◽  
Welding Current ◽  
Empirical Models ◽  
Seam Tracking ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Time Data ◽  
On Line ◽  
Arc Welding Process

Recently, not only robotic welders have replaced human welders in many welding applications, but also reasonable seam tracking systems are commercially available. However, fully adequate process control systems have not been developed due to a lack of reliable sensors and mathematical models that correlate welding parameters to the bead geometry for the automated welding process. Especially, real-time quality control in automated welding process is an important factor contributing to higher productivity, lower costs and greater reliability of the bead geometry. In this paper, on-line empirical models with experimental results are proposed in order to be applicable for the prediction of bead geometry. For development of the proposed predicting model, an attempt has been made to apply for a several methods. For the more accurate prediction, the prediction variables are first used to the surface temperatures measured using infrared thermometers with the welding parameters (welding current, arc voltage, CTWD and gas flow rate) because the surface temperature are strongly related to the formation of the bead geometry. And the developed model has been carried out a learning each time data acquired.

A study on welding quality for the automatic vertical-position welding process based on Mahalanobis Distance method

2018 ◽  
Vol 1 (91) ◽  
pp. 31-40
Author(s):  
B.-J. Jin ◽  
M.-H. Park ◽  
T.-J. Yun ◽  
J.-Y. Shim ◽  
B.-Y. Kang ◽  
...  
Keyword(s):  
Mahalanobis Distance ◽  
Welding Process ◽  
Welding Current ◽  
Welding Parameters ◽  
Vertical Position ◽  
Welding Quality ◽  
Distance Method ◽  
Arc Voltage ◽  
On Line ◽  
Arc Welding Process

Purpose: The welding quality and reducing production cost could be achieved by developing the automatic on-line welding quality monitoring system. However, investigation of welding fault to quantify the welding quality on the horizontal-position welding has been concentrated. Therefore, MD (Mahalanobis Distance) method on the vertical-position welding process by analysing the transform arc voltage and welding current gained from the on-line monitoring system has been applied. Design/methodology/approach: The transformed welding current and arc voltage data were taken from the experiment whereby the data number was 2500 data/s. The prediction of Contact Tip to Work Distance (CTWD) to gain best welding quality using the waveform variations were then taken from the experimental results. MD was employed to quantify the welding quality by analysing the transformed arc voltage and welding current. Finally, the optimal CTWD setting has verified the developed algorithms through additional experiments. Two kinds of experiments has been carried out by changing welding parameters artificially to verify the sensitivity and feasibility of WQ (Welding Quality) based on the concepts of MD and normal distribution. Findings: The results represented that WQ was fully capable of quantifying and qualifying the welding faults for automatic vertical-position welding process. Research limitations/implications: The arc welding process on the vertical-position compared to a horizontal-position welding is much more difficult because the metal transfer is influenced by the gravity force. To solve the problem, a new algorithm to monitor and control the welding fault during the arc welding process has been developed. Furthermore, optimization of welding parameters for the vertical-position welding process was really difficult to use the developed algorithms because they are only useful in selecting stored data and not for evaluating the effect of the variation of welding parameters on the weld ability. Practical implications: The developed algorithm could be achieved the highest welding quality at 15mm CTWD setting which the welding quality is 99.50% for the start section and 99.68% at the middle section. Originality/value: This paper proposed a new algorithm which employed the concepts of MD (Mahalanobis Distance) and normal distribution to describe a good quality welding.

scholarly journals Optimization of TIG Welding Parameters for the 202 Stainless Steel Using NSGA-II

2020 ◽  
Vol 8 (4) ◽  
Author(s):  
Neeraj Sharma ◽  
◽  
Wathiq Sleam Abduallah ◽  
Manish Garg ◽  
Rahul Dev Gupta ◽  
...  
Keyword(s):  
Tensile Strength ◽  
Flow Rate ◽  
Gas Flow ◽  
Welding Process ◽  
Welding Current ◽  
Welding Parameters ◽  
Shielding Gas ◽  
Gas Flow Rate ◽  
Electrode Diameter ◽  
Weld Region

Tungsten Inert Gas welding is a fusion welding process having very wide industrial applicability. In the present study, an attempt has been made to optimize the input process variables (electrode diameter, shielding gas, gas flow rate, welding current, and groove angle) that affect the output responses, i.e., hardness and tensile strength at weld center of the weld metal SS202. The hardness is measured using Vicker hardness method; however, tensile strength is evaluated by performing tensile test on welded specimens. Taguchi based design of experiments was used for experimental planning, and the results were studied using analysis of variance. The results show that, for tensile strength of the welded specimens, welding current and electrode diameter are the two most significant factors with P values of 0.002 and 0.030 for mean analysis, whereas higher tensile strength was observed when the electrode diameter used was 1.5 mm, shielding gas used was helium, gas flow rate was 15 L/min, welding current was 240A, and a groove angle of 60o was used. Welding current was found to be the most significant factor with a P value of 0.009 leading to a change in hardness at weld region. The hardness at weld region tends to decrease significantly with the increase in welding current from 160-240A. The different shielding gases and groove angle do not show any significant effect on tensile strength and hardness at weld center. These response variables were evaluated at 95% confidence interval, and the confirmation test was performed on suggested optimal process variable. The obtained results were compared with estimated mean value, which were lying within ±5%.

INVESTIGATION OF TENSILE BEHAVIOUR OF TIG WELDED 316 STAINLESS STEEL USING TAGUCHI TECHNIQUES

2019 ◽  
Vol 14 (4) ◽  
Author(s):  
Karthimani T ◽  
Babu N
Keyword(s):  
Stainless Steel ◽  
Welding Speed ◽  
Gas Flow ◽  
Welding Process ◽  
Welding Current ◽  
Tig Welding ◽  
Filler Material ◽  
Tensile Behaviour ◽  
Welding Parameters ◽  
Taguchi Technique

This works aims at the analysis and optimization of joining similar grades of stainless steel by TIG welding. TIG welding may use a filler material. There is a variant in the process which does not require filler material. Such process is known as Autogenous TIG welding process. The parameters like current, welding speed and gas flow rate are the variables in the study. The objective of this research is to determine the influence of various welding parameters on the weld bead of 316 SS by using Taguchi technique. A plan of experiments based on Taguchi technique method has been carried out. Orthogonal array, signal to noise (S/N) Ratio, Analysis of variance (ANOVA) are employed for studying the welding characteristics of material & to optimize the weld parameters. The result obtained are the output from each parameter, through which optimal parameters are found out for maximum tensile strength. It is found that -welding current followed by welding speed are major parameters influencing mechanical properties of welded joint

Application of Microcomputers to Automatic Weld Quality Control

1980 ◽  
Vol 102 (2) ◽  
pp. 62-68 ◽  
Author(s):  
M. Tomizuka ◽  
D. Dornfeld ◽  
M. Purcell
Keyword(s):  
Control Method ◽  
Computer Control ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Seam Tracking ◽  
Process Time ◽  
Welding Parameters ◽  
Weld Quality ◽  
On Line ◽  
Welding Processes

The demand for increased productivity of welding operations has led to the expanded use of computer control to allow higher production rates while maintaining weld quality. The charateristics of the gas metal arc welding process and the relationship between welding parameters, the desired output of the welding process, and the automation of the process are discussed. A strategy for two-axis welding torch positioning and velocity control is developed based on preview control techniques. To evaluate the applicability of the proposed control method the motion of heat source along different welding paths is simulated on an analog computer with on-line control of process time constants by an LSI-11 microcomputer. The simulation results show that high quality seam tracking can be accomplished by controlling the torch motion using the proposed method. The method appears to be suitable for on-line control of welding processes.

scholarly journals Comparison between PCA analysis and Grey based Taguchi analysis of TIG welding process parameters on Duplex stainless steel

2021 ◽  
pp. 67-74
Author(s):  
Sandip Mondal ◽  
Goutam Nandi ◽  
Pradip Kumar Pal
Keyword(s):  
Stainless Steel ◽  
Duplex Stainless Steel ◽  
Process Parameters ◽  
Gas Flow ◽  
Welding Process ◽  
Principal Component ◽  
Welding Current ◽  
Tig Welding ◽  
Welding Parameters ◽  
Welding Quality

Tungsten inert gas (TIG) welding on Duplex stainless steel (DSS) is more easy, comfortable and useful, if the process is precisely understood and controlled through development of the science & technology. TIG welding on DSS has been performed with the help of specific controlled welding process parameters. Welding quality has been strongly depended on these process parameters. In this study, some valuable welding parameters are chosen. These are welding current, shielding gas flow rate and speed of welding. These process parameters of TIG welding for ASTM/UNS 2205 DSS welds are optimized by using Principal Component Analysis (PCA) method and Grey based Taguchi’s L9 Orthogonal array (OA) experimental plan with the conception of signal to noise ratio (N/S). After that, compression results of above mentioned two analyses of TIG welding process parameters have been calculated. The quality of the TIG welding on DSS has been evaluated in term of ultimate tensile strength, yield strength and percentage of elongation. Compression results of both analyses indicate application feasibility for continuous improvement of welding quality on DSS in different components of chemical, oil and gas industries.

scholarly journals Analysis of Current on Mechanical Properties and Microstructure of A53 Gr B Material with Gas Tungsten Arc Welding Process

Teknik ◽  
2021 ◽  
Vol 42 (1) ◽  
pp. 20-28
Author(s):  
Tarmizi Tarmizi ◽  
Yudha Bakti Nugraha ◽  
Irfan Irfan
Keyword(s):  
Mechanical Properties ◽  
Arc Welding ◽  
Gas Flow ◽  
Welding Process ◽  
Welding Current ◽  
Gas Tungsten Arc Welding ◽  
Correct Process ◽  
Gas Tungsten Arc ◽  
Gas Tungsten ◽  
Arc Welding Process

The welding use correct process parameters will produce joint with optimum in mechanical properties. The current is a very important process parameter in welding. Gas Tungsten Arc Welding process carbon steel A53 Gr B uses current variations can be an option to get the best quality joints. The purpose of this research is to get optimum mechanical properties and microstructure by varying the current. The experimental method uses GTAW process by varying current in welding A 53 Gr B using a single V butt joint and a 5G welding position, the Argon protective gas flow rate of 15 liters per minute with filler rod ER 70 S-6. This process also uses 11-13 Volt voltage with DCEN polarity and current 70, 90, and 110A. Based on ASME Section IX, the test results show that the specimen with a current of 90A gives optimum results with a tensile strength of 480 MPa and a hardness value of 190 HV, whereas specimens with welding current of 70A bring incomplete penetration defects in the weld area. The use of welding current 90A in this research provides welding results with better mechanical properties and microstructure compared to the use of currents of 70 and 110A

A Study on Welding Quality of Robotic Arc Welding Process Using Mahalanobis Distance Method

2013 ◽  
Vol 773-774 ◽  
pp. 759-765 ◽  
Author(s):  
Reenal Ritesh Chand ◽  
Ill Soo Kim ◽  
Ji Hye Lee ◽  
Jong Pyo Lee ◽  
Ji Yeon Shim ◽  
...  
Keyword(s):  
Process Parameters ◽  
Mahalanobis Distance ◽  
Arc Welding ◽  
Gma Welding ◽  
Welding Process ◽  
Experimental Results ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Welding Quality ◽  
Arc Welding Process

In robotic GMA (Gas Metal Arc) welding process, heat and mass inputs are coupled and transferred by the weld arc and molten base material to the weld pool. The amount and distribution of the input energy are basically controlled by the obvious and careful choices of welding process parameters in order to accomplish the optimal bead geometry and the desired mechanical properties of the quality weldment. To make effective use of automated and robotic GMA welding, it is imperative to predict online faults for bead geometry and welding quality with respect to welding parameters, applicable to all welding positions and covering a wide range of material thickness. To successfully accomplish this objective, two sets of experiment were performed with different welding parameters; the welded samples from SM 490A steel flats adopting the bead-on-plate technique were employed in the experiment. The experimental results of current and voltage waveforms were used to predict the magnitude of bead geometry and welding quality, and to establish the relationships between weld process parameters and online welding faults. MD (Mahalanobis Distance) technique is employed for investigating and modeling of GMA welding process and significance test techniques were applied for the interpretation of the experimental data. Statistical models developed from experimental results which can be used to control the welding process parameters in order to achieve the desired bead geometry based on weld quality criteria.

Diffusible Hydrogen Control in Flux Cored Arc Welding Process

2013 ◽  
Vol 597 ◽  
pp. 171-178 ◽  
Author(s):  
Dariusz Fydrych ◽  
Aleksandra Świerczyńska ◽  
Jacek Tomków
Keyword(s):  
Welding Process ◽  
Welding Current ◽  
Welding Parameters ◽  
Hydrogen Degradation ◽  
Diffusible Hydrogen ◽  
Cored Wire ◽  
Flux Cored Arc Welding ◽  
Deposited Metal ◽  
Relevant Variables ◽  
Arc Welding Process

One of the types of hydrogen degradation of steel welded joints is cold cracking. The direct cause of the formation of cold cracks is simultaneous presence of hydrogen, residual stresses and brittle structure. The way of preventing the occurring of degradation is to eliminate at least one of these factors. Practice has shown that the best solution is to control the amount of hydrogen in deposited metal. In this paper an experimental evaluation of the effect of the welding parameters on the content of diffusible hydrogen in deposited metal obtained from rutile flux cored wire grade H10 was carried out. The state of the art of considered issues was described and results of preliminary investigations were presented. Five factors were considered: the flow rate of shielding gas, the welding current, the arc voltage, the welding speed and the electrode extension. All factors were optimized using a Plackett-Burman design to get the most relevant variables. The level of diffusible hydrogen was determined by a glycerin test. The results of the experiment indicate that appropriate choice of welding parameters may significantly reduce diffusible hydrogen content in deposited metal.

A Study on Development of the Optimal Neural Network in GMA Welding Process

2014 ◽  
Vol 936 ◽  
pp. 1759-1763
Author(s):  
Qian Qian Wu ◽  
Ji Hye Lee ◽  
Jong Pyo Lee ◽  
Min Ho Park ◽  
Young Su Kim ◽  
...  
Keyword(s):  
Neural Network ◽  
Process Parameters ◽  
Gma Welding ◽  
High Reliability ◽  
Welding Process ◽  
Welding Current ◽  
Welding Parameters ◽  
Welding Quality ◽  
Optimal Parameters ◽  
On Line

Gas Metal Arc (GMA) welding is considered as a multi-parameter process that it’s hard to find optimal parameters for good welding. To overcome the problem, an artificial neural network based on the backpropagation algorithm was built to realize the relationships between process parameters and welding quality as output parameter. In this study, Mahalanobis Distance (MD) was employed to evaluate the availability of a given welding parameters which was proved to performance well in multivariate statistics. Input parameters such as welding current and arc voltage were chosen due to their significant influence on the welding quality. To improve the precision of given parameters’ evaluation, neural networks with different configurations were verified. The analyses on the measured and predicted MD by the proposed neural network were conducted. The proposed neural network based on the error backpropogation algorithm was proved to have high reliability to evaluate process parameters, which further makes it available in on-line monitoring system.

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