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Numerical simulation and experimental validation of the welding operation of the railcar bogie frame to prevent distortion

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Abstract

The need for an efficient welding process which is fast, safe, cost-effective and will produce a welded structure that combines high strength with integrity during railcar manufacturing is necessary due to the increasing demand and complexity of the manufacturing process. In this study, the Taguchi method and response surface methodology (RSM) were used for the numerical experimentation design of a railcar bogie frame. The modelling and simulation of the railcar bogie frame was conducted using the Commercial Abaqus software 2018. Using the Taguchi method, the designed experiment consists of an orthogonal array of four factors varied over three levels with the welding parameters in the following ranges: voltage (22–25 V), current (200–250 A), speed (0.01 m/s) and arc length (0.03–0.07 m) as input variables. The matrix generated nine experimental runs whose weld distortions were determined via the physical experimentations. Also, the RSM was used to study the cross effect of the input welding parameters on the welded structure. The statistical analysis of the results obtained brought about the development of a predictive model for the determination of weld distortion as function of the independent welding input parameters. In addition, the results indicate that the input welding parameters are critical factors that affect welding processes significantly, hence the need for control. This work will assist manufacturers in the quest for effective process control during the welding operation.

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References

  1. Huang H, Ma N, Murakawa H (2014) Fast prediction of welding distortion using ISM and i-ISM with validation by experiment: 24th International Ocean and Polar Engineering Conference, June 15–20, Busan, Korea; 2014

  2. Wahid MA, Khan NZ, Sharma N (2017) Effect of CNC milling machining parameters on depth of pocket. Global Sci-Tech 9:1–7

    Article  Google Scholar 

  3. Sharma N, Khan ZA, Siddiquee AN, Shihab SK, Wahid MA (2018a) Effect of process parameters on microstructure and electrical conductivity during FSW of Al-6101 and pure copper. Mater Res Express 5:1–12

    Google Scholar 

  4. Farkas J, Jamai K (2007) Special cases of the calculation of residual welding distortions. pp 70–73

  5. Michaleris P (2011) Minimization of welding distortion and buckling. Woodhead Publishing. pp 3

    Chapter  Google Scholar 

  6. Hui-Jun Yi H-J, Kim J-Y, Yoon J-H, Kang S-S (2011) Investigations on welding residual stress and distortion in a cylinder assembly by means of a 3D finite element method and experiments. J Mech Sci Technol 25(12):3185–3193

    Article  Google Scholar 

  7. Yaghi AH, Hyde TH, Becker AA, Sun W (2013) Finite element simulation of residual stresses induced by the dissimilar welding of a P92 steel pipe with weld metal IN625. Int J Press Vessel Pip 111–112:173–186

    Article  Google Scholar 

  8. Long H, Gery D, Carlier A, Maropoulos PG (2009) Prediction of welding distortion in butt joint of thin plates. Mater Des 4126–4135

    Article  Google Scholar 

  9. Zeinoddini M, Arnavaz S, Zandi AP, Vaghasloo YA (2013) Repair welding influence on offshore pipelines residual stress fields: an experimental study. J Constr Steel Res 86:31–41

    Article  Google Scholar 

  10. Song S, Dong P (2017) Residual stresses at weld repairs and effects of repair geometry. Sci Technol Weld Join 22:265–277

    Article  Google Scholar 

  11. Hu Y, Chen Y, Li L, Hu H, Zhu Z (2016) Microstructure and properties of Al/Cu bimetal in liquid−solid compound casting process. Trans Nonferrous Metals Soc China 26:1553–1563

    Google Scholar 

  12. Nata A, Babu S (2012) Finite element simulation of hybrid welding process for welding 304 austenitic stainless steel plate. IJRET 1(3):101–410

    Google Scholar 

  13. Hosseinzadeh F, Bouchard PJ (2013) Map** multiple components of the residual stress tensor in a large P91 steel pipe girth weld using a single contour cut. Exp Mech 53:171–181

    Article  Google Scholar 

  14. Sun TZ, Roy MJ, Strong D, Withers PJ, Prangnell PB (2017) Comparison of residual stress distributions in conventional and stationary shoulder high-strength aluminum alloy friction stir welds. J Mater Process Technol 242:92–100

    Article  Google Scholar 

  15. Chougule MN, Somase SC (2014) Experimental and analytical study of thermally induced residual stresses for stainless steel grade using GMAW process. 5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12th -14th, 2014, IIT Guwahati, Assam, India. pp 674–679

  16. Liu C, Zhu HY, Dong CL (2014) Internal residual stress measurement on inertia friction welding of nickel-based super alloy. Sci Technol Weld Join 19:408–415

    Article  Google Scholar 

  17. Xu WH, Lin SB, Fan CL, Yang CL (2015) Prediction and optimization of weld bead geometry in oscillating arc narrow gap all-position GMA welding. Int J Adv Manuf Technol 79:183–196

    Article  Google Scholar 

  18. Kartal ME, Kang Y-H, Korsunsky AM, Cocks ACF, Bouchard JP (2016) The influence of welding procedure and plate geometry on residual stresses in thick components. Int J Solids Struct 80:420–429

    Article  Google Scholar 

  19. Smith M, Levesque J-B, Bichler L, Sediako D, Gholipour J, Wanjara P (2017) Residual stress analysis in linear friction welded in-service Inconel 718 super alloy via neutron diffraction and contour method approaches. Mater Sci Eng 691:168–179

    Article  Google Scholar 

  20. Qiao D, Zhang W, Pan TY, Crooker P, David S, Feng Z (2013) Evaluation of residual plastic strain distribution in dissimilar metal weld by hardness map**. Sci Technol Weld Join 18(7):624–630

    Article  Google Scholar 

  21. Liang W, Murakawa H, Deng D (2015) Investigation of welding residual stress distribution in a thick-plate joint with an emphasis on the features near weld end-start. Mater Des 67:303–312

    Article  Google Scholar 

  22. Turski M, Francis JA, Hurrenll PR, Bate SK, Hiller S, Withers PJ (2012) Effects of stop start features on residual stresses in a multi-pass austenitic stainless steel weld. Int J Press Vessel Pip 89:9–18

    Article  Google Scholar 

  23. Deng D, Kiyoshima S (2014) Influence of annealing temperature on calculation accuracy of welding residual stress in a SUS304 stainless steel joint. Acta Metall Sin 50(5):626–632

    Google Scholar 

  24. Kozak J, Kowalski J (2015) Problems of determination of welding angular distortions of T-fillet joints in ship hull structures. Pol Marit Res 2(86)22:79–85

    Article  Google Scholar 

  25. Vasantharaja P, Maduarimuthu V, Vasudevan M, Palanichamy P (2012) Assessment of residual stresses and distortion in stainless steel weld joints. Mater Manuf Process 27:1376–1381

    Article  Google Scholar 

  26. Pamnani R, Vasudevan M, Jayakumar T, Vasantharaja P, Ganesh KC (2016) Numerical simulation and experimental validation of arc welding of DMR-249A steel. Def Technol 12:305–315

    Article  Google Scholar 

  27. Derakhshan ED, Yazdian N, Craft B, Smith S, Kovacevic R Numerical simulation and experimental validation of residual stress and welding distortion induced by laser-based welding processes of thin structural steel plates in butt joint configuration. Opt Laser Technol 104:170–182

    Article  Google Scholar 

  28. Dal M, Fabbro R (2016) An overview of the state of art in laser welding simulation. Opt Laser Technol 78:2–14

    Article  Google Scholar 

  29. Chukkan JR, Vasudevan M, Muthukumaran S, Kumar RR, Chandrasekhar N (2015) Simulation of laser butt welding of AISI 316L stainless steel sheet using various heat sources and experimental validation. J Mater Process Technol 219:48–59

    Article  Google Scholar 

  30. Pozo LP, Fernando OZ, Orlando DA (2015) Optimization of welding parameters using a genetic algorithm: a robotic arm–assisted implementation for recovery of Pelton turbine blades. Adv Mech Eng 7(11):1–17

    Google Scholar 

  31. Aworanti OA, Agarry SE, Ajani AO (2013) Statistical optimization of process variables for biodiesel production from waste cooking oil using heterogeneous base catalyst. Br Biotechnol J 3(2):116–132

    Article  Google Scholar 

  32. Enweremadu CC, Rutto HL (2015) Optimization and modelling of process variables of biodiesel production from marula oil using response surface methodology. J Chem Soc Pak 37(2):256–265

    Google Scholar 

  33. Bello EI, Ogedengbe TI, Lajide L, Daniyan IA (2016) Optimization of process parameters for biodiesel production using response surface methodology. Am J Energy Eng 4(2):8–16

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Industrial Engineering, Tshwane University of Technology, Pretoria, 0001, South Africa

    Ilesanmi Daniyan & Khumbulani Mpofu

  2. Department of Mechanical and Automation Engineering, Tshwane University of Technology, Pretoria, 0001, South Africa

    Festus Fameso

  3. Department of Mechanical & Mechatronics Engineering, Afe Babalola University, Ado Ekiti, Nigeria

    Adefemi Adeodu

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  1. Ilesanmi Daniyan
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  2. Khumbulani Mpofu
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  4. Adefemi Adeodu
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Correspondence to Ilesanmi Daniyan.

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Daniyan, I., Mpofu, K., Fameso, F. et al. Numerical simulation and experimental validation of the welding operation of the railcar bogie frame to prevent distortion. Int J Adv Manuf Technol 106, 5213–5224 (2020). https://doi.org/10.1007/s00170-020-04988-6

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  • DOI: https://doi.org/10.1007/s00170-020-04988-6

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