Development of Mathematical Models to Analyse and Predict Weld Bead Geometry and Shape Relationships in FCA Welding of C-45 Mild Steel
DOI:
https://doi.org/10.22486/iwj/2018/v51/i4/176798Keywords:
ANOVA, Design of Experiments, Wire Feed Rate, Weld Dilution, GMAW Welding.Abstract
Welding plays an extremely important role in fabrication industry because of its adaptability to automation, relative simplicity, strong and reliable joints and ability to weld a large variety of materials making it widely acceptable in construction, transport, automotive and pressure vessel industry. A wide variety of arc welding processes are available to cater to the needs of ever increasing industrial demands. GMAW is one such arc welding process which has proved its significance in industry owing to its versatility and quality of joints. The physical dimensions and shape of a weld joint not only decides its mechanical strength but also affects its performance during service. Sufficient knowledge of various bead parameters such as penetration, reinforcement, width, etc. becomes imperative along with their dependence on various welding parameters constituting voltage, feed rate of wire and speed of welding. In the present research work, an attempt was made to form a mathematical model for bead geometry prediction at given values of weld input parameters. Statistical techniques have been applied for the present investigation work.
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References
Ghogale MM and Patil SA (2013); Optimisation of process parameters of MIG welding to improve quality of weld by using Taguchi methodology, International Journal of Engineering Research and Technology, 2(12), pp.36773685.
Welding Handbook (1978); American Welding Society, 2(2).
Ghosh A and Hloch S (2013); Prediction and optimization of yield parameters for submerged arc welding process, Technical Gazette, 2(20), pp.213-216.
Mishra D, Manjunath A and Parthiban K (2017); Interpulse TIG welding of titanium alloy (Ti-6Al-4V), Indian Welding Journal, 50(4), pp.56-71.
Irfan S and Achwal V (2014); An experimental study on the effect of MIG welding parameters on the weldability of galvanized steel, International Journal on Emerging Technologies, 5(1), pp.146-152.
Gupta VK and Parmar RS (1986); Fractional factorial technique to predict dimensions of the weld bead in automatic submerged arc welding, Journal of Institution of Engineers (India), Mechanical Engineering Division, 70, pp.67-71.
Davies OL (1978); The Design and Analysis of Industrial Experiments, Second edition Longman Press, New York.
Murugan N and Gunaraj V (2005); Prediction and control of weld bead geometry and shape relationships in submerged arc welding of pipes, Journal of Materials Processing Technology, 168(3), pp. 478-487.
Kamble AG and Rao RV (2013); Experimental investigation on the impacts of process parameters of GMAW and transient thermal analysis of AISI321 steel, Advances in Manufacturing, 1(4), pp.362-377.
Kannan T (2009); Effect of process parameters on clad bead geometry and its shape relationships of stainless steel claddings deposited by GMAW, International Journal of Advanced Manufacturing Technology, 47(9-12), pp.1083-1095.