The Effect of Thread Throat Diameter of Welding Bolt on Weld Defect Formation and its Optimization in Projection Welding

Year 2025, Volume: 5 Issue: 3, 123 - 128

Hilal Kır , Mustafa Yazar , Şükrü Talaş

https://doi.org/10.64808/engineeringperspective.1753998

Abstract

The welding process plays a critical role in the joining of sheet metal parts in the automotive industry, as in other manufacturing sectors. In this study, a welding defect observed in M6x21 weld bolts joined by projection welding—utilizing the protrusion geometry on the fasteners was investigated. The joining was carried out using 3 mm thick WSS-M1A365-A22 sheet steel and 8.8 grade M6x21 weld bolts; however, insufficient weld strength and low rupture loads were detected. Analytical evaluations revealed that the root cause of the defect was the contact between the bolt geometry and the sheet sur-face, which caused the welding current to dissipate over a wide area. To eliminate this issue, an M6x26 weld bolt with a smaller thread root diameter and longer thread length was used in the welding process. In order to ensure adequate rupture strength in projection welding with the M6x26 bolt, welding process parameters were investigated. The Taguchi L9 orthogonal array was used to evaluate three different welding currents (26, 28, 30 kA) and three different welding forces (400, 500, 600 daN), with the cycle time kept constant. The rupture load results were analyzed using the “larger-the-better” crite-rion, and the optimum welding parameters were determined as 600 daN welding force and 30 kA welding current. However, considering energy efficiency in the production environment, it was concluded that a current of 28 kA and a force of 600 daN also provided sufficient weld strength. Scanning Electron Microscope (SEM) analyses enabled microstructural evaluation of weld region defects.

Keywords

Weld bolt , Projection welding , SEM analysis , Taguchi method

Ethical Statement

The authors must declare that there is no conflict of interest in the study.

Supporting Institution

Şahinkul Machine and Spare Parts Manufacturing Co. Ltd.

Project Number

ARGE-2023-036 2300790000

Thanks

This study was supported by Şahinkul Makine in frame of the project code of ARGE-2023-036 2300790000 as researchers, Scholarship in this study was supported by TÜBİTAK BİDEB (Turkish Scientific and Technological Research Council, Scien-tist Support Department) (Project No: 119C053).

References

• 1. Zhou, K. & Yao, P. (2017). Review of application of the electrical structure in resistance spot welding. in IEEE Access. vol. 5. 25741-25749. doi: 10.1109/ACCESS.2017.2771310.
• 2. Wang, X. & Zhang, Y. (2017). Effects of welding procedures on resistance projection welding of nuts to sheets. ISIJ International.57 (12). 2194-2200. https://doi.org/10.2355/isijinternational.ISIJINT-2017-219.
• 3. Han, G., Ha, S., Marimuthu, K.P., Murugan, S.P., Park, Y., Lee, H. (2021). Shape optimation of square weld nut in projection welding. The International Journal of Advanced Manufacturing Technology. 113. pages 1915-1928. https://doi.org/10.1007/s00170-021-06771-7
• 4. Jha, K., Tamang, S.K., Kumar, R., Choudhury, B., A comprehensive analysis of influencing factors and the role of modelling and optimiza-tion for improved quality. New Materials, Processing and Manufac-turability: Fabrication and Processing of Advanced Materials, En-hancing Resistance Spot Welding Weld Quality. Chapter 5. Book Editor(s):R. Thanigaivelan, Pradeep Kumar Krishnan, Kamalakanta Muduli, Santosh Kumar Tamang, 25.07.2024, https://doi.org/10.1002/9781394212736.ch5
• 5. Melakhsou, A.A., Hubert, M.B. (2021). On welding defect detection and causalities between welding signals. 2021 IEEE 17th Interna-tional Conference on Automation Science and Engineering (CASE). 23-27 August 2021. Lyon, France, DOI: 10.1109/CASE49439.2021.9551659
• 6. Yazar, M., Kır, H., & Talaş, Ş. (2025). The Effect of Welding Wire Feed Speed on Weld Bead Penetration, Length and Width in Robotic Gas Metal Arc Welding. Engineering Perspective, 5(2), 85-89. https://doi.org/10.29228/eng.pers.81420
• 7. Madhvacharyula, A.S., Pavan, A.V. S., Gorthi, S., Chitral, S., Ven-kaiah, N., Kiran, D.V. (2022). In situ detection of welding defects: a review. Welding in the World. vol. 66. pages 611-628. https://doi.org/10.1007/s40194-021-01229-6
• 8. Mercan, Serdar (2019). Failure analysis of weld joints. International Journal of Innovative Engineering Applications. 3 (2). 67-75.
• 9. Mandal, N.R. (2017). Welding Defects. In: Ship Construction and Welding. Springer Series on Naval Architecture, Marine Engineering, Shipbuilding and Shipping. vol 2. Springer. Singapore. https://doi.org/10.1007/978-981-10-2955-4_19
• 10. Sharma, S., Anitha, D., Chaturvedi, V., Vimal, J., Jayaswal, P., Saxena, K.K., Aherwar, A., Pathak, V.K., Abdullaev, S.S. (2024). MIG welding process parameter optimisation of AISI 1026 steel us-ing Taguchi-TOPSIS method. International Journal on Interactive Design and Manufacturing (IJIDeM). Vol 18, pages 1345-1357. https://doi.org/10.1007/s12008-023-01528-w.
• 11. Yelamasetti, B., Sandeep, M., Narella, S.S., Tiruchanur, V.V., Sonar, T., Prakash, C., Shelare, S., Mubarak, N.M., Kumar, S. (2024). Op-timization of TIG welding process parameters using Taguchi tech-nique for the joining of dissimilar metals of AA5083 and AA7075. Scientific Reports 14. 23694. https://doi.org/10.1038/s41598-024-74458-6.
• 12. Rojas, H., Vargas, Z., Valdez, S., Serrano, M., Pozo, A.D., Alcánta-ra., M. (2024). Taguchi, Grey Relational Analysis, and ANOVA Op-timization of TIG Welding Parameters to Maximize Mechanical Per-formance of Al-6061 T6 Alloy. J. Manuf. Mater. Process. 8(6). 246. https://doi.org/10.3390/jmmp8060246 .
• 13. Ahmad, A., Alam, S. (2019). Integration of RSM with Grey based Taguchi Method for optimization of pulsed TIG welding process pa-rameters. Materials Today: Proceedings. Vol 18. Part 7. Pages 5114-5127. https://doi.org/10.1016/j.matpr.2019.07.508.
• 14. Yüce, Celalettin. (2021) . Multi-objective optimisation for indentation rate, nugget diameter and tensile load in resistance spot welding using Taguchi-based grey relational analysis. International Journal of Mate-rials and Product Technology. Vol 63. No 4. pp 321-338. https://doi.org/10.1504/IJMPT.2021.118352.
• 15. Li, X. & Simpson, S.W. (2009). Parametric approach to positional fault detection in short arc welding. Science and Technology of Weld-ing and Joining. 14 (2). 146-151. https://doi.org/10.1179/136217108X370272
• 16. Das, P.P. & Chakraborty, S. (2023). Optimisation of friction stir welding processes using hybrid-taguchi methods: a comparative anal-ysis. International Journal on Interactive Design and Manufacturing (IJIDeM). 17. 1021-1038. https://doi.org/10.1007/s12008-022-01017-6
• 17. Nobrega, G., Souza, M.S., Martín, M.R., Gonzálvez P.R., Ribeiro, J. (2021). Parametric optimisation of the GMAW welding process in thin thickness of austenitic stainless steel by Taguchi Method. Ap-plied Sciences. 11(18). 8742. https://doi.org/10.3390/app11188742
• 18. Koal, J., Baumgarten, M., Nikolov, C., Ramakrishnan, S., Mathiszik, C., Schmale, H.C. (2024). Acoustic process monitoring during pro-jection welding using airborne sound analysis and machine learning. Welding in the World. https://doi.org/10.1007/s40194-024-01876-5
• 19. Mathiszik, C., Koal, J., Zschetzsche, J., Füssel, U., Schmale, H.C. (2024). Non-destructive characterisation of resistance projection welded joints by ultrasonic and passive magnetic flux density testing. Welding in the World. 68. 2671-2682. https://doi.org/10.1007/s40194-024-01808-3
• 20. Bıyık, A., İnce, U., Ateş, F., Yetilmezsoy, K. (2016). Determination of optimal process parameters for reduction of spatter in joining of weld bolts by projection welding by Taguchi and Multi-Objective Optimisation Methods. Engineer and Machinery. volume 57. number 677. pp. 36-52.
• 21. Yazar, M., Alp, A.K., Talaş, Ş. (2020). Effect of electrode thrust force on spot quality of DP600 steels in projection Fwelding. Aca-demic Perspective Procedia. 3(1). 16-24. DOI:10.33793/acperpro.03.01.9