Open Access
Subscription Access
Open Access
Subscription Access
Application of Artificial Neural Networks in Predicting Output Parameters of Gas Metal Arc Welding of Dissimilar Steels
Subscribe/Renew Journal
Artificial Neural Network (ANN) can be used for prediction utilizing some learning method. Gas metal arc welding (GMAW) was reported in a previous work to join SS304L stainless steel and EN8 mild steel plates. The experimental data obtained are used for training the ANN to enable it predict the output. ANN model is constructed to estimate ultimate tensile strength, elongation and hardness of the weld joint. A data set is tested through the modeled ANN to have satisfactory results. Quite close estimation of the ANN predicted values can be made with the observed ultimate tensile strength, elongation and hardness of the weld joint.
Keywords
GMAW, ANN, Dissimilar Welding, MIG, Modeling, MATLAB.
User
Subscription
Login to verify subscription
Font Size
Information
- P Kah and Martikainen, Trends in Joining Dissimilar Metals by Welding, Applied Mechanics and Material, Vol 440, page 269-276.
- A Karim and Y D Park, A Review on Welding of Dissimilar Metals in Car Body Manufacturing, Journal of Welding and Joining, Vol. 38, page 370-384, 2020.
- M Marya, A Brief Review of Challenges & Technologies to Weld Dissimilar Metals in Two industries: The Upstream Oil & Gas and the Automotive, Materials Science Forum, page 155-158, 2008.
- P G Chaudhari and J D Patel, Evaluate the Metal Inert Gas Welding using Activated Flux on SS316L by ANN, Processing of Asian Studies, page 221-232, 2016.
- J Lee and K Um, A Comparison in a Back-Bead Prediction of Gas Metal Arc Welding Using Multiple Regression Analysis and Artificial Neural Network, Journal of Optics and Lasers in Engineering, Vol 34, page 149-158, 2000.
- J Shah, G Patel and J Makwana, Optimization and Prediction of MIG Welding Process Parameters Using ANN, International Journal of Engineering Development and Research, Vol 5, page 1487-1491, 2017.
- N A Basim, N R Raj, S J Sajin, W V Pradeep and S V Nagaraj, Experimental Investigation of MIG Welding Parameters and its Mechanical Properties on Dissimilar Steels, International Journal of Engineering Science and Computing, Vol 7, page 9989-9991, 2017.
- B Chan, J Pacey and M Bibby, Modelling Gas Metal Arc Weld Geometry Using Artificial Neural Network Technology, Journal of Canadian Metallurgical Quarterly, Vol 38, page 43-51, 1999.
- P Kah, J Suoranta and J Martikainen, Advanced Gas Metal Arc Welding Process, The International Journal of Advanced Manufacturing Technology, Springer Nature Switzerland AG, Vol 67, page 655-674, 2012.
- O P Khanna, A Text of Welding Technology, Dhanpat Rai Publications, New Delhi, 2001.
- S Pal, S K Pal and A K Samantaray, Artificial Neural Network Modeling of Weld Joint Strength Prediction of a Pulsed Metal Inert Gas Welding Process Using Arc Signals, Journal of Materials Processing Technology, Vol 202, page 464-474, 2008.
- D S Nagesh and G L Datta, Modeling of Fillet Welded Joint of GMAW Process: Integrated Approach Using DOE, ANN and GA, International Journal on Interactive Design Manufacturing, Vol 2, page 127-136, 2008.
- P Sreeraj, T Kannan and S Maji, Simulation and Parameter Optimization of GMAW Process Using Neural Networks and Particle Swarm Optimization Algorithm, International Journal of Mechanical Engineering and Robotic Research, Vol 2, page 131-146, 2013.
- R Addamani, H V Ravindra and S K Gayathri devi, Estimation and Comparison of Welding Performances for ASTM A 106 Material in P-GMAW Using GMDH and ANN, Journal of Critical Reviews, Vol 7, page 2606-2613, 2020.
- D Ramos-Jaime and I Lopez-Juarez, ANN and Linear Regression Model Comparison for the Prediction of Bead Geometrical Properties in Automated Welding, 1st International Congress on Instrumentation and Applied Science, page 1-10, 2010.
- O Bataineh, A Shoubaki and O Barquawi, Optimising Process Conditions in MIG Welding of Aluminum Alloys Through Factorial Design Experiments, Latest Trends in Environmental and Manufacturing Engineering, page 21-26, 2012.
- V Singh, M Chandrasekaran and M Thirugananasambandam, Artificial Neural Network Modelling of Weld Bead Characteristics during GMAW of Nitrogen Strengthened Austenitic Stainless Steel, AIP Conference Proceedings 2128, 020024, 2019.
- P Sreeraj and T Kannan, Modelling and Prediction of Stainless-Steel Clad Bead Geometry Deposited by GMAW Using Regression and Artificial Neural Network Models, Advances in Mechanical Engineering, Vol 4, page 1-12, 2015.
- B N Sreeharan, T Kannan and P Aravind, Process Optimization of GMAW over AA6351 Aluminium Alloy Using ANN, Vol 8, page 208-218, 2017.
- M Singhmar and M Verma, Experimental Study for Welding Aspects of Austenitic Stainless Steel (AISI 304) on Hardness by Taguchi Technique, International Journal of Advance Engineering and Research Development, Vol 2, page 114-123, 2015.
Abstract Views: 699
PDF Views: 0