The present work addresses the feasibility of friction stir spot welding (FSSW) of metallic aluminum alloy (Al6061) to thermoplastic polycarbonate (PC) sheets using a tapered pin tool incorporating real-time process monitoring with thrust-torque signals. Sensitivity analysis identified axial tool thrust during dwelling as the most superior indicator for joint integrity (≥ 40.1%) due to its role in enhancing interfacial mixing and bonding. The tool revolving speed primarily governs the process stability (≥ 30.9%) and thus predominantly enhances the weld strength (36.5 MPa) through controlled materials stirring. In contrast, dwell time governs the joint ductility (35.5%) by promoting adequate consolidation, while plunge depth dictates the weld hardness (43%) through prolonged deformation along dissimilar interface. An integrated multi-criteria decision-making (MCDM) analysis using ARAS, TOPSIS, and GRA provided consistent optimization trends with a strong rank correlation coefficient (> 0.9), confirming methodological reliability. The findings establish a quantitative framework for optimizing FSSW of dissimilar Al-PC, offering a validated approach for achieving improved mechanical behaviour through balanced process stability.
PaolettiALambiaseFDi IlioA. Analysis of forces and temperatures in friction spot stir welding of thermoplastic polymers. The International Journal of Advanced Manufacturing Technology2016; 83: 1395–1407.
2.
KumarRSinghRAhujaIPS, et al.Friction-stir-spot welding of 3D printed ABS and PA6 composites: flexural, thermal, and morphological investigations. Advances in Materials and Processing Technologies2022; 8: 909–916.
3.
SahuSKMishraDPalK. A comparative study between weldability of polycarbonate and nylon-6 using different pin geometries in friction stir welding. Proc Inst Mech Eng B J Eng Manuf2022; 236: 522–539.
4.
SchmidtHHattelJWertJ. An analytical model for the heat generation in friction stir welding. Model Simul Mat Sci Eng2004; 12: 143–157.
5.
HannachiNKhalfallahALeitãoC, et al.Thermo-mechanical modelling of the friction stir spot welding process: effect of the friction models on the heat generation mechanisms. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications2022; 236: 1464–1475.
6.
GuptaSDasSNarayananRG, et al.Friction stir spot welding of dissimilar quality galvanized steel sheets meant for automotive applications using a consumable sheet. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering2023; 237: 1517–1528.
7.
MertŞArıcıA. Design of optimal joining for friction stir spot welding of polypropylene sheets. Sci Technol Weld Joining2011; 16: 522–527.
8.
SahuSKMishraDPalK, et al.Multi sensor based strategies for accurate prediction of friction stir welding of polycarbonate sheets. Proc Inst Mech Eng C J Mech Eng Sci2021; 235: 3252–3272.
9.
SahuSKMishraDPalK. Optimizing process parameters for joint strength efficiency improvement in friction stir welding of polycarbonate sheets. Materwiss Werksttech2021; 52: 739–761.
10.
GoswamiNPalK. Comparative assessment on weldability of Al 6061 to polycarbonate for dissimilar sheets placement in friction stir lap welding using sensor signals. Proc Inst Mech Eng C J Mech Eng Sci2021; 236: 3475–3496.
11.
BagheriBAbbasiMHamzelooR. The investigation into vibration effect on microstructure and mechanical characteristics of friction stir spot vibration welded aluminum: simulation and experiment. Proc Inst Mech Eng C J Mech Eng Sci2020; 234: 1809–1822.
12.
BagheriBMahdian RiziAAAbbasiM, et al.Friction stir spot vibration welding: improving the microstructure and mechanical properties of Al5083 joint. Metallography, Microstructure, and Analysis2019; 8: 713–725.
13.
BagheriBAbbasiMGiviM. Effects of vibration on microstructure and thermal properties of friction stir spot welded (FSSW) aluminum alloy (Al5083). Int J Prec Eng Manuf2019; 20: 1219–1227.
14.
MahmoudABehrouzB. New attempt to improve friction stir brazing. Mater Lett2021; 304: 130688.
15.
BagheriBAbbasiMAbdollahzadehA, et al.Advanced approach to modify friction stir spot welding process. Met Mater Int2020; 26: 1562–1573.
16.
AkbariMHassanzadehESavaripourH. Real-time monitoring of friction stir welding: a review of current practices. Weld World2025; 11. DOI: 10.1007/s40194-025-02120-4
17.
AkbariMAbdollahzadehAEsfandiarM. A comprehensive review of material flow in FSW/FSP: Experimental insights and simulation perspectives. Engineering Reports2025; 7: 2577–8196.
18.
AkbariMEsfandiarMAbdollahzadehA. The role of force and torque in friction stir welding: a detailed review. Journal of Advanced Joining Processes2025; 11: 100289.
19.
BiliciMKYüklerAİKurtulmuşM. The optimization of welding parameters for friction stir spot welding of high density polyethylene sheets. Mater Des2011; 32: 4074–4079.
20.
ShojaeefardMHKhalkhaliAAkbariM, et al.Investigation of friction stir welding tool parameters using FEM and neural network. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications2015; 229: 209–217.
21.
AkbariMHassanzadehEAslYD, et al.A comprehensive review on the integration of artificial intelligence in friction stir welding for monitoring, modelling, and process optimization. Journal of Advanced Joining Processes2025; 11: 100316.
22.
ÇalışkanHKurşuncuBKurbanoğluC, et al.Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods. Mater Des2013; 45: 473–479.
23.
OduGO. Weighting methods for multi-criteria decision making technique. Journal of Applied Sciences and Environmental Management2019; 23: 1449.
24.
BarikTParidaSPalK. Optimizing process parameters in drilling of CFRP laminates: a combined MOORA–TOPSIS–VIKOR approach. Fibers and Polymers2024; 25: 1859–1876.
25.
SaatyRW. The analytic hierarchy process—what it is and how it is used. Math Model1987; 9: 161–176.
26.
JulongD. Introduction to grey systems theory. The Journal of Grey System1989; 1: 1–24.
27.
NiranjanTSingaravelBSrinivasulu RajuS. Optimization of hole quality parameters using TOPSIS method in drilling of GFRP composite. Mater Today Proc2022; 62: 2109–2114.
28.
ZavadskasEKTurskisZ. A new additive ratio assessment (ARAS) method in multicriteria decision-making / NAUJAS ADITYVINIS KRITERIJŲ SANTYKIŲ ĮVERTINIMO METODAS (ARAS) DAUGIAKRITERINIAMS UŽDAVINIAMS SPRĘSTI. Technological and Economic Development of Economy2010; 16: 159–172.
29.
BarbosaCECBatistaMBatalhaGF, et al.Friction stir spot welding lap-shear force analysis of automotive low-carbon steel sheets joint. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering2024. Epub ahead of print 26 February 2024. DOI: 10.1177/09544089241234553.
30.
GaoJMeiXDongJ, et al.Effects of the processing parameters and laser textures in friction stir spot welding of al alloy and polyimide joints. Proc Inst Mech Eng B J Eng Manuf2025; 239: 821–833.
31.
MertSAriciA. Design of optimal joining for friction stir spot welding of polypropylene sheets. Sci Technol Weld Joining2011; 16: 522–527.
32.
OduGO. Weighting methods for multi-criteria decision making technique. Journal of Applied Sciences and Environmental Management2019; 23: 1449.
33.
WięckowskiJSałabunW. Sensitivity analysis approaches in multi-criteria decision analysis: A systematic review. Appl Soft Comput2023; 148: 110915. Epub ahead of print 1 November 2023. DOI: https://doi.org/10.1016/j.asoc.2023.110915.
34.
TranQ-PNguyenV-NHuangS-C. Drilling process on CFRP: multi-criteria decision-making with entropy weight using grey-TOPSIS method. Appl Sci2020; 10: 7207.
35.
VaratharajuluMDuraiselvamMKumarMB, et al.Multi criteria decision making through TOPSIS and COPRAS on drilling parameters of magnesium AZ91. Journal of Magnesium and Alloys2022; 10: 2857–2874.
36.
ShanianASavadogoO. TOPSIS multiple-criteria decision support analysis for material selection of metallic bipolar plates for polymer electrolyte fuel cell. J Power Sources2006; 159: 1095–1104.
37.
WeiG. Grey relational analysis model for dynamic hybrid multiple attribute decision making. Knowl Based Syst2011; 24: 672–679.
38.
RajmohanTPalanikumarKPrakashS. Grey-fuzzy algorithm to optimise machining parameters in drilling of hybrid metal matrix composites. Compos B Eng2013; 50: 297–308.
39.
DattaSBandyopadhyayAPalPK. Grey-based taguchi method for optimization of bead geometry in submerged arc bead-on-plate welding. The International Journal of Advanced Manufacturing Technology2008; 39: 1136–1143.
40.
DellingerJ. Correlation, Spearman. In: Correlation, spearman. In The sage encyclopedia of communication research methods. SAGE Publications, Inc, pp. 274–275.
41.
ShenZDingYGerlichAP. Advances in friction stir spot welding. Crit Rev Solid State Mater Sci2020; 45: 457–534.
42.
AbdollahzadehABagheri VananiBKoohdarH, et al.Multi-pass friction stir welding of Al–TiC–Zn–Mg Composite: microstructure and mechanical characteristics. Metallography, Microstructure, and Analysis2024; 13: 601–623.
43.
AbdollahzadehABagheri VananiBMasoudi MorghmalekiA, et al.Advancements in joining Al-Zn-TiC-Mg composites using friction stir welding process: influence of traverse speed. J Compos Mater2024; 58: 2757–2779.
44.
PachecoMRKabcheJPThesiI, et al.Temperature distribution analysis in plates joined by friction stir welding. In: Volume 11: mechanics of solids, structures and fluids.Lake buena vista, Florida, USA: ASMEDC, 2009, pp.163–169.
45.
AbdollahzadehAVananiBBKoohdarH, et al.Influence of variation ambient system on dissimilar friction stir welding of Al alloy to Mg alloy by the addition of nanoparticles and interlayer. Met Mater Int2024; 30: 2830–2852.
46.
PattanaikAKPradhanSPandaSN, et al.Effect of process parameters on friction stir spot welding using grey based Taguchi methodology. Mater Today Proc2018; 5: 12098–12102.
47.
VananiBBAbdollahzadehAAbbasiM, et al.Zn interlayer and tool offset effects on IMC formation and strength of AA5083/AZ91Mg joints via friction stir vibration welding. The International Journal of Advanced Manufacturing Technology2025; 141: 551–577.
48.
Bagheri VananiBAbdollahzadehA. Fabrication of reinforced Al–Mg composite by TiC particles via FSW: microstructure and tribology study. J Mater Res Technol2024; 30: 6787–6801.
49.
PrabhakarDAPKorgalAShettigarAK, et al.A review of optimization and measurement techniques of the friction stir welding (FSW) process. Journal of Manufacturing and Materials Processing2023; 7: 181.
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