Development of mathematical models for predicting mechanical properties of dissimilar DP600 steel and AZ31B magnesium alloy friction stir welds

This study presents the development of mathematical models for predicting the mechanical properties of dissimilar DP600 steel-AZ31B magnesium alloy friction stir welded joints. A General Full Factorial Design was employed by considering rotational speed, welding speed, and tool offset as process parameters. Ultimate tensile strength (UTS), yield strength (YS), microhardness (HV), and percentage elongation (%E) were selected as response variables. Second-order polynomial regression models were developed using Python, and their adequacy was evaluated through ANOVA. The developed models exhibited high predictive capability with R² values greater than 0.94 for all responses. The optimum welding condition was obtained at a rotational speed of 765 rpm, welding speed of 31.5 mm/min, and tool offset of 1.5 mm, producing a maximum UTS of 185.708 MPa, YS of 130.506 MPa, microhardness of 207.9 HV, and elongation of 4.508%. The results indicated that rotational speed and tool offset positively influenced the mechanical properties, whereas welding speed showed a comparatively negative effect. The close agreement between experimental and predicted values confirmed the reliability of the developed mathematical models for predicting and optimizing the mechanical performance of dissimilar friction stir welded joints.

friction stir welding; DP600 steel; AZ31B magnesium alloy; mathematical modeling

1. W. M. Thomas, E. D. Nicholas, J. C. Needham, M. G. Church, P. Templesmith, and C. J. Dawes, “The Welding Institute,” TWI, Int. Pat. Appl. no. pct/GB92/02203 GB Pat. Appl., no. 912598.8, 1991. [Google Scholar] [Crossref]

2. K. Elangovan, V. Balasubramanian, and S. Babu, “Predicting tensile strength of friction stir welded AA6061 aluminium alloy joints by a mathematical model,” Mater. Des., vol. 30, no. 1, pp. 188–193, 2009, doi: 10.1016/j.matdes.2008.04.037. [Google Scholar] [Crossref]

3. N. S. Sundaram and N. Murugan, “Dependence of ultimate tensile strength of friction stir welded AA2024-T6 aluminium alloy on friction stir welding process parameters,” Mechanics, vol. 78, no. 4, pp. 17–24, 2009. [Google Scholar] [Crossref]

4. N. Babu, N. Karunakaran, and V. Balasubramanian, “A study to estimate the tensile strength of friction stir welded AA 5059 aluminium alloy joints,” Int. J. Adv. Manuf. Technol., vol. 93, no. 1, pp. 1–9, 2017. [Google Scholar] [Crossref]

5. Y. Abe, T. Watanabe, H. Tanabe, and K. Kagiya, “Dissimilar metal joining of magnesium alloy to steel by FSW,” Adv. Mater. Res., vol. 15–17, pp. 393–397, 2007, doi: 10.4028/www.scientific.net/amr.15-17.393. [Google Scholar] [Crossref]

6. H. Kasai, Y. Morisada, and H. Fujii, “Dissimilar FSW of immiscible materials: Steel/magnesium,” Mater. Sci. Eng. A, vol. 624, 2015, doi: 10.1016/j.msea.2014.11.060. [Google Scholar] [Crossref]

7. S. Joo, “Joining of dissimilar AZ31B magnesium alloy and SS400 mild steel by hybrid gas tungsten arc friction stir welding,” Met. Mater. Int., vol. 19, no. 6, pp. 1251–1257, 2013, doi: 10.1007/s12540-013-6016-9. [Google Scholar] [Crossref]

8. T. Wang, S. Shukla, B. Gwalani, M. Komarasamy, L. Reza-Nieto, and R. S. Mishra, “Effect of reactive alloy elements on friction stir welded butt joints of metallurgically immiscible magnesium alloys and steel,” J. Manuf. Process., vol. 39, no. November 2018, pp. 138–145, 2019, doi: 10.1016/j.jmapro.2019.02.009. [Google Scholar] [Crossref]

9. A. Heidarzadeh, T. Saeid, H. Khodaverdizadeh, and A. Mahmoudi, “Establishing a Mathematical Model to Predict the Tensile Strength of Friction Stir Welded Pure Copper Joints,” vol. 44, no. FEBRUARY, 2013, doi: 10.1007/s11663-012-9755-y. [Google Scholar] [Crossref]

10. A. Gill, D. Parkash, V. Gulati, and S. Sharma, “Mathematical Modeling Of Process Parameters Of Friction Stir Welded Aluminium Alloy Joints Using Central Composite Design,” Mater. Today Proc., vol. 5, no. 14, pp. 27865–27876, 2018, doi: 10.1016/j.matpr.2018.10.025. [Google Scholar] [Crossref]

11. R. Palanivel, P. K. Mathews, and N. Murugan, “Development of mathematical model to predict the ultimate tensile strength of friction stir welded dissimilar aluminum alloy,” vol. 18, no. 5, pp. 517–523, 2012. [Google Scholar] [Crossref]

12. B. Bora, S. Chattopadhyaya, and R. Kumar, “Development of mathematical model for friction stir welded joint using ‘ R ’ Programming,” Mater. Today Proc., no. xxxx, p. 5, 2019, doi: 10.1016/j.matpr.2019.09.083. [Google Scholar] [Crossref]

13. S. N. Pandya and J. V Menghani, “Developments of mathematical models for prediction of tensile properties of dissimilar AA6061-T6 to Cu welds prepared by friction stir welding process using Zn interlayer,” Sādhanā, vol. 0123456789, 2018, doi: 10.1007/s12046-018-0928-5. [Google Scholar] [Crossref]

14. H. I. Joshi and G. D. Acharya, “Numerical investigation of design parameters influence on stress distributions in horizontal multi-saddle cylindrical pressure vessel,” Mater. Today Proc., vol. 5, no. 9, pp. 19480–19489, 2018, doi: 10.1016/j.matpr.2018.06.309. [Google Scholar] [Crossref]

15. H. I. Joshi and G. D. Acharya, “Design of experiment approach for stress assessment in saddle supported pressure vessels,” Int. J. Adv. Eng. Res. Dev., pp. 375–380, 2017. [Google Scholar] [Crossref]

• Machine Learning Based Surface Roughness Prediction for Parameters of ECM
• Non-Newtonian Characterization of Gelatinized Corn Starch Dispersions with Magnetic Particle Enhancement Under Shear Stress
• Performance, Evaluation and Optimization of Biodiesel from Desert Date Oil Using Response Surface Methodology
• Performance Evaluation of Ceno-TiO₂/Al Electrodes in Continuous Electrocoagulation of Automobile Wash Wastewater
• Weld Formation Investigations of FSW of Al 6061-T6 Lapped Workpieces Using Dual Shoulders Tool