scholarly journals Application of Taguchi Method in Optimization of Pulsed TIG Welding Process Parameter

2020 ◽  
Author(s):  
Asif Ahmad
Keyword(s):  
Manufacturing Industry ◽  
Welded Joint ◽  
Welding Process ◽  
Pulse Frequency ◽  
Process Parameter ◽  
Tig Welding ◽  
Bead Width ◽  
Aisi 316 ◽  
Arc Welding Process ◽  
Pulsed Tig Welding

Pulsed TIG welding is one of the most widely used welding processes in the metal manufacturing industry. In any fusion arc welding process, the bead width plays an important role in determining the welding strength and mechanical properties of the weld joint. This study present optimization of the pulsed TIG welding process parameter using Taguchi Philosophy. AISI 316/3136L austenite stainless steel 4mm is used for welding and for the establishment of the optimum combination of the process parameter and depending upon the functional requirement of the welded joint, the acceptable welded joint should have optimum bead width and minimum heat affected zone (HAZ) etc. An experiment was conducted using different welding condition and a mathematical model was constructed using the data collected from the experiment based on Taguchi L25 orthogonal array. Optimum parameter obtained for bead width is peak current 180 ampere, base current 100 ampere, pulse frequency 125Hz and pulse on time 40%.

Optimization of Argon Gas Metal Arc Welding Process Parameters with Regard to Tensile Strength for AISI 310 Stainless Steel Using Taguchi Technique

2022 ◽  
Vol 58 ◽  
pp. 1-10
Author(s):  
Hanmant Virbhadra Shete ◽  
Sanket Dattatraya Gite
Keyword(s):  
Tensile Strength ◽  
Arc Welding ◽  
Welded Joint ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Taguchi Technique ◽  
Argon Gas ◽  
Metal Arc Welding ◽  
310 Stainless Steel ◽  
Arc Welding Process

Gas metal arc welding (GMAW) is the leading process in the development of arc welding process for higher productivity and quality. In this study, the effect of process parameters of argon gas welding on the strength of T type welded joint of AISI 310 stainless steel is analyzed. The Taguchi technique is used to develop the experimental matrix and tensile strength of the welded joint is measured using experimental method and finite element method. Optimization of input parameter is performed for the maximum tensile strength of welded joint using ANOVA. The results showed that welding speed is the most significant factor affecting the tensile strength followed by voltage in argon gas metal arc welding (AGMAW) process. Argon gas welding process performance with regard to the tensile strength is optimized at voltage: 18.5 V, wire feed speed: 63 m/min and welding speed: 0.36 m/min.

scholarly journals Development of an Artificial Intelligence Powered TIG Welding Algorithm for the Prediction of Bead Geometry for TIG Welding Processes using Hybrid Deep Learning

Metals ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 451
Author(s):  
Martin A. Kesse ◽  
Eric Buah ◽  
Heikki Handroos ◽  
Godwin K. Ayetor
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Deep Neural Network ◽  
Predictive Accuracy ◽  
Welding Process ◽  
Tig Welding ◽  
Bead Geometry ◽  
Bead Width ◽  
Modeling Tools ◽  
Welding Processes

Recent developments in artificial intelligence (AI) modeling tools allows for envisaging that AI will remove elements of human mechanical effort from welding operations. This paper contributes to this development by proposing an AI tungsten inert gas (TIG) welding algorithm that can assist human welders to select desirable end factors to achieve good weld quality in the welding process. To demonstrate its feasibility, the proposed model has been tested with data from 27 experiments using current, arc length and welding speed as control parameters to predict weld bead width. A fuzzy deep neural network, which is a combination of fuzzy logic and deep neural network approaches, is applied in the algorithm. Simulations were carried out on an experimental test dataset with the AI TIG welding algorithm. The results showed 92.59% predictive accuracy (25 out of 27 correct answers) as compared to the results from the experiment. The performance of the algorithm at this nascent stage demonstrates the feasibility of the proposed method. This performance shows that in future work, if its predictive accuracy is improved with human input and more data, it could achieve the level of accuracy that could support the human welder in the field to enhance efficiency in the welding process. The findings are useful for industries that are in the welding trade and serve as an educational tool.

Optimization of Flux Cored Arc Welding Process Parameter Using Genetic and Memetic Algorithms

2013 ◽  
Vol 13 (4) ◽  
pp. 239-250 ◽  
Author(s):  
T. Kannan ◽  
N. Murugan ◽  
B. N. Sreeharan
Keyword(s):  
Arc Welding ◽  
Welding Process ◽  
Memetic Algorithms ◽  
Optimization Techniques ◽  
Low Carbon ◽  
Robotic Welding ◽  
Bead Width ◽  
Flux Cored Arc Welding ◽  
Arc Welding Process ◽  
Welding Processes

AbstractMost of the manufacturing enterprises indulge in the bonding of metals during the production process. This makes welding one of the most important processes in industries. Subsequently, due to the high usage of welding process, industrial engineers desire to optimize the parameters concerned to achieve the desired weld bead characteristics. This paper focuses on optimization of flux cored arc welding process parameters, which are used for deposition of duplex stainless steel on low carbon structural steel plates. Experiments were conducted based on central composite rotatable design and mathematical models were developed using multiple regression method. Further, optimization with objectives as minimizing percentage dilution, maximizing height of reinforcement and bead width was carried out using genetic algorithm and memetic algorithm. This problem was formulated as a multi objective, multivariable and non-linear programming problem. The algorithms were implemented using basic functions of C language making it highly reliable, adoptable, very user friendly and extendable to other welding processes such as GMAW, GTAW, robotic welding, etc. The adopted optimization techniques were further compared based on various computational factors.

scholarly journals A Study on On-line Mathematical Model to Control of Bead Width for Arc Welding Process

2017 ◽  
Vol 174 ◽  
pp. 68-73 ◽  
Author(s):  
Joon Sik Son ◽  
Jong-Pyo Lee ◽  
Min-Ho Park ◽  
Byeong-Ju Jin ◽  
Tae-Jong Yun ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Arc Welding ◽  
Welding Process ◽  
Bead Width ◽  
On Line ◽  
Arc Welding Process

Effect of Process Parameter on Tensile Strength of Spot Welded S235 Sheet Using Simulation and Experimental

2020 ◽  
Vol 899 ◽  
pp. 169-179
Author(s):  
Mohd Nazri Yusuf ◽  
Wan Emri Wan Abdul Rahman ◽  
Yupiter H.P. Manurung
Keyword(s):  
Tensile Strength ◽  
Welded Joint ◽  
Simulation Analysis ◽  
Fem Simulation ◽  
Welding Process ◽  
Process Parameter ◽  
Low Carbon ◽  
Premature Failure ◽  
Optimum Result ◽  
Spot Welded

This study focused on investigation of the effect of process parameter to the tensile strength of a spot welded S235 low carbon steel through simulation and experiment. Resistance spot welding (RSW) is commonly used in joining metal sheets due to its key capabilities, which is time and cost effective as well as high adaptability for automation. However, strength and reliability of a spot welded joint especially in an auto vehicle can be unpredictable. Premature failure of a spot welded joint can be difficult to be predicted but common factors that had been discussed in many research is related with fatigue and residual stress. Process parameter is recognized as one of critical factors affecting the reliability and quality of a spot welded joint. Different type of material and thickness may require different set of parameter to achieve an optimum result. Experimental procedure alone to demonstrate and investigate the effect could be too costly and time inefficient. Therefore, design of experiment and non-linear FEM simulation analysis were used to analyze and validate the result. This study shows the significance of process parameters such as weld current and electrode pressure to the strength of a spot welded joint and accurate setting is needed prior to the welding process to achieve an optimum result.

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