Skip to main content
SpringerLink
Log in

Hybrid multi-response optimization of friction stir spot welds: failure load, effective bonded size and flash volume as responses

  • Published:
Sādhanā Aims and scope Submit manuscript

Abstract

Friction stir spot welding (FSSW) is a multi-input multi-response process. Effective multi-response optimization of welds is desirable to create welds with a balance of quality responses. In order to eliminate the subjectivity (uncertainty and engineering judgment) with the existing multi-response Taguchi-based Grey relational analysis, principal component analysis (PCA) was integrated into it. The PCA helps in determining the effective optimal weighting values required for the estimation of Grey relational grade (GRG). As a result, tool rotational speed, plunge depth and dwell time were employed as input parameters while failure load (FL), expelled flash volume (EFV) and effective bonded size (EBS) of conical pin friction stir spot-welded joint of AA2219-O alloy were the chosen output responses. EFV was minimized while FL and EBS of the joints were maximized using this hybrid multi-response approach. From the analysis of variance of GRG and its response graphs, the significant parameters and their levels were obtained. Experimental results confirmed the effectiveness and robustness of this method. In addition, three critical zones were observed on the fracture surfaces of joints, namely, tool impelled unbonded zone, partially bonded zone and effective bonded/nugget zone. The weld nugget failed by circumferential nugget shear mode.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6

Similar content being viewed by others

References

  1. Bozkurt Y 2012 The optimization of friction stir welding process parameters to achieve maximum tensile strength in polyethylene sheets. Mater. Des. 35: 440–445

    Article  Google Scholar 

  2. Ojo O O, Taban E and Kaluc E 2015 Friction stir spot welding of aluminium alloys: a recent review. Mater. Test. 57(7–8): 609–627

    Article  Google Scholar 

  3. Paidar M, Khodabandeh A, Najafi H and Rouh-aghdam A S 2015 An investigation on mechanical and metallurgical properties of 2024-T3 aluminum alloy spot friction welds. Int. J. Adv. Manuf. Technol. 80(1–4): 183–197

    Article  Google Scholar 

  4. Palani K and Elanchezhian C 2015 Multi response optimization of process parameters on AA8011 friction stir welded aluminium alloys using RSM based GRA coupled with DEA. Appl. Mech. Mater. 813–814: 446–450

    Article  Google Scholar 

  5. Taban E, Kaluc E 2007 Comparison between microstructure characteristics and joint performance of 5086-H32 aluminium alloy welded by MIG, TIG and friction stir welding processes. Kov. Mater. Met. Mater. 45(5): 241–248

    Google Scholar 

  6. Vijayan D and Rao V S 2014 A multi-response optimization of tool pin profile on the tensile behaviour of age-hardenable aluminium alloys during friction stir welding. Res. J. Appl. Sci. Eng. Technol. 7(21): 4503–4518

    Google Scholar 

  7. Lakshminarayanan A K and Balasubramanian V 2008 Process parameters optimization for friction stir welding of RDE-40 aluminium alloy using Taguchi technique. Trans. Nonferr. Met. Soc. China 18: 548–554

    Article  Google Scholar 

  8. Oladimeji O O and Taban E 2016 Trend and innovations in laser beam welding of wrought aluminum alloys. Weld. World 60(3): 415–457

    Article  Google Scholar 

  9. Yuvaraj K P and Senthilkumar B 2014 Experimental investigation and optimization of friction stir welding process—a review. Appl. Mech. Mater. 550: 39–47

    Article  Google Scholar 

  10. Elatharasan G and Kumar V S S 2012 Modelling and optimization of friction stir welding parameters for dissimilar aluminium alloys using RSM. Procedia Eng. 38: 3477–3481

    Article  Google Scholar 

  11. Rambabu G, Naik D B, Rao C H V, Rao K S and Reddy G M 2015 Optimization of friction stir welding parameters for improved corrosion resistance of AA2219 aluminium alloy joints. Def. Technol. 11: 330–337

    Article  Google Scholar 

  12. Mustafa F F, Kadhym A H and Yahya H H 2015 Tool geometries optimization for friction stir welding of AA6061-T6 aluminum alloy T-joint using Taguchi method to improve the mechanical behaviour. J. Manuf. Sci. Eng. 137(3): 031018

    Article  Google Scholar 

  13. Dinaharan I and Murugan N 2012 Optimization of friction stir welding process to maximize tensile strength of AA6061/ZrB2 in-situ composite butt joints. Met. Mater. Int. 18(1): 135–142

    Article  Google Scholar 

  14. Elanchezhian C, Ramnath B V, Venkatesan P, Sathish S, Vignesh T, Siddharth R V, Vinay B and Gopinath K 2014 Parameter optimization of friction stir welding of AA8011-6062 using mathematical method. Procedia Eng. 97: 775–782

    Article  Google Scholar 

  15. Kesharwani R K, Panda S K and Pal S K 2014 Multi objective optimization of friction stir welding parameters for joining of two dissimilar thin aluminum sheets. Procedia Mater. Sci. 6: 178–187

    Article  Google Scholar 

  16. Kumar S and Kumar S 2014 Multi-response optimization of process parameters for friction stir welding of joining dissimilar Al alloys by gray relation analysis and Taguchi method. J. Braz. Soc. Mech. Sci. Eng. 37(2): 665–674

    Article  Google Scholar 

  17. Mehat N M, Kamaruddin S and Othman A R 2014 Hybrid integration of Taguchi parametric design, grey relational analysis, and principal component analysis optimization for plastic gear production. Chin. J. Eng. 2014: 1–11

    Article  Google Scholar 

  18. Fung C and Kang P 2005 Multi-response optimization in friction properties of PBT composites using Taguchi method and principal component analysis. J. Mater. Process. Technol. 170: 602–610

    Article  Google Scholar 

  19. Ojo O O, Taban E and Kaluc E 2016 Understanding the role of welding parameters and tool profile on the morphology and properties of expelled flash of spot welds. Mater. Des. 108: 518–528

    Article  Google Scholar 

  20. Shojaeefard M H, Akbari M, Khalkhali A and Asadi P 2014 Optimization of microstructural and mechanical properties of friction stir welding using cellular automation and Taguchi method. Mater. Des. 64: 660–666

    Article  Google Scholar 

  21. Saini S K and Pradhan S K 2014 Optimization of multi-objective response during CNC turning using Taguchi-Fuzzy application. Procedia Eng. 97: 141–149

    Article  Google Scholar 

  22. Raza Z A, Ahmad N and Kamal S 2014 Multi-response optimization of rhamnolipid production using Grey rational analysis in Taguchi method. Biotechnol. Rep. 3: 86–94

    Article  Google Scholar 

  23. Kazancoglu Y, Esme U, Bayramoglu M, Guven O and Ozgun S 2011 Multi-objective optimization of the cutting forces in turning operations using the grey-based Taguchi method. Mater. Technol. 45(2): 105–110

    Google Scholar 

  24. Durairaj M, Sudharsun D and Swamynathan N 2013 Analysis of process parameters in wire EDM with stainless steel using single objective Taguchi method and multi-objective grey relational grade. Procedia Eng. 64: 868–877

    Article  Google Scholar 

  25. Ghosh S, Sahoo P and Sutradhar G 2013 Tribological performance optimization of Al-7.5% SiCp composites using the Taguchi method and grey relational analysis. J. Compos. 2013: 1–9

    Article  Google Scholar 

  26. Jayaraman P and Kumar L M 2014 Multi-response optimization of machining parameters of turning AA6063 T6 aluminium alloy using Grey relational analysis in Taguchi method. Procedia Eng. 97: 197–204

    Article  Google Scholar 

  27. Reddy V C, Deepthi N and Jayakrishna N 2015 Multi-response optimization of wire EDM on aluminium HE30 by using Grey relational analysis. Mater. Today Proc. 2: 2548–2554

    Article  Google Scholar 

  28. Mustaji M I, Prasetyo T, Ilhamsah H W and Sugiono R S 2015 Optimizing multi-response green machining using Taguchi method based on grey relational analysis. Appl. Mech. Mater. 747: 277–281

    Article  Google Scholar 

  29. Singh H, Kamboj A and Kumar S 2014 Multi-response optimization in drilling Al6063/SiC/15% metal matrix composite. Int. J. Chem. Nucl. Mater. Metall. Eng. 8(4): 281–286

    Google Scholar 

  30. Jailani H S, Rajadurai A, Mohan B, Kumar A S and Sornakumar T 2009 Multi-response optimisation of sintering parameters of Al–Si alloy–fly ash composite using Taguchi method and grey relational analysis. Int. J. Adv. Manuf. Technol. 45(3–4): 362–369

    Article  Google Scholar 

  31. Bobbili R, Madhu V and Gogia A K Multi-response optimization of wire-EDM process parameters of ballistic grade aluminium alloy. Eng. Sci. Technol. Int. J. 18(4): 720–726

  32. Jolliffe I T 2002 Principal component analysis, 2nd ed. New York: Springer-Verlag Inc

    MATH  Google Scholar 

  33. Smith L I 2002 A tutorial on principal components analysis. URL: www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf accessed on 2nd March 2016

  34. Shlens J 2014 A tutorial on principal component analysis. Mountain View, CA: Google Research. URL: http://arxiv.org/pdf/1404.1100.pdf accessed 3rd March 2016

  35. Roy R K 2001 Design of experiment using the Taguchi approach: 16 steps to product and process improvement. New York: John Wiley and Sons

    Google Scholar 

  36. Lin P C, Pin J and Pan T 2008 Failure modes and fatigue life estimations of spot fatigue welds in lap shear specimens of aluminium 6111-T4 sheets. Part 1: welds made by a concave tool. Int. J. Fatigue 30(1): 74–89

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by a grant from Scientific Research Project Support-Unit of Kocaeli University (grant no. 2015/71 HD), Turkey. The authors would like to thank Mr. Onur Birbasar of the R&D Department, Assan Aluminium, Istanbul, Turkey, for his valuable support.

Author information

Authors and Affiliations

  1. The Federal University of Technology Akure, Akure, Ondo State, Nigeria

    O O OJO

  2. Kocaeli University, Izmit, Kocaeli, Turkey

    O O OJO & E TABAN

  3. Welding Research Education and Training Centre, Kocaeli University, Izmit, Turkey

    E TABAN

Authors
  1. O O OJO
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. E TABAN
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to O O OJO.

Ethics declarations

Ethical statement/declaration

This work was the expansion of our previous work titled “Understanding the role of welding parameters and tool profile on the morphology and properties of expelled flash of spot welds”.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

OJO, O.O., TABAN, E. Hybrid multi-response optimization of friction stir spot welds: failure load, effective bonded size and flash volume as responses. Sādhanā 43, 98 (2018). https://doi.org/10.1007/s12046-018-0882-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12046-018-0882-2

Keywords

Search

Navigation