Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Application of Response Surface Methodology for Modeling of Laser Transformation Hardening of Commercially Pure Titanium ASTM Grade3


Affiliations
1 School of Mechanical Engineering, Dr. A. D. Shinde Institute of Technology, Guddai, Bhadgaon − 416502, Gadhinglaj, Kolhapur, Maharashtra, India
     

   Subscribe/Renew Journal


In the presented study, the laser transformation hardening of commercially pure titanium sheet material of thickness being 1.6mm is investigated using CW, 1.6 kW solid State Nd: YAG laser. A Full Factorial Design (FFD) with Response Surface Methodology (RSM) is employed to establish, optimize and to investigate the relationships of three laser transformation hardening process parameters such as laser power, scanning speed, and focused position on laser hardened bead profile parameters such as hardened bead width, hardened depth, heat input and power density. In this work, Laser Transformation Hardening (LTH) with high precision and an optimum desired minimum value of hardened depth of 241 microns has been accomplished with heat input = 150 J/cm and power density = 294.08 W/mm2 for the laser process parameters of lower beam power: 750 Watts, high scanning speed: 3000 mm/min and a defocused beam of –30 mm. Effects of laser process parameters on laser hardened bead geometries were carried out using RSM. Results indicate that the scanning speed has a positive effect on all hardened bead dimensions while the laser power has a positive effect particularly on hardened bead width as compared to hardened depth and heat input. The optimum laser hardening conditions are identified sequentially to minimise hardened depth, heat input, power density and maximum hardened bead width. The validation results demonstrate that the developed models are accurate with low percentages of error.

Keywords

Analysis of Variance, Bead Geometry, Full Factorial Design, Laser Transformation Hardening, Response Surface Methodology.
Subscription Login to verify subscription
User
Notifications
Font Size


  • D.S. Badkar, K.S. Pandey and G. Buvanashekaran. Int. J. of Transactions of Nonferrous Metals Soc. of China, 20, 1078 (2010). https://doi.org/10.1016/S1003-6326(09)60261-2.
  • U. Reisgen, M. Schleser, O. Mokrov and E. Ahmed. Optimization of laser welding of DP/TRIP steel sheets using statistical approach, Optics & Laser Tech., 44, 255 (2012). https://doi.org/10.1016/j.optlastec.2011.06.028.
  • K. Pal, S. Bhattacharya and S.K. Pal. Int. J. of Com. Intd. Manufg., 24, 198 (2011). https://doi.org/10.1080/0951192X.2010.542181.
  • G. Padmanaban and V. Balasubramanian. Int. J. of Transactions of Nonferrous Metals Soc. of China, 21, 467 (2011). https://doi.org/10.1016/S1003-6326(11)60738-3.
  • P.S Kumar, S. Rao and A. Ramakrishna. J. of Mech. Engg Res., 3, 186 (2011).
  • X.Y. Zhang and Y.S. Zhang. Adv. Mats Res., 211-212, 1110 (2011). https://doi.org/10.4028/www.scientific.net/AMR.211-212.1110.
  • R. Palanivel, P. Koshy Mathews and N. Murugan. J. of Engg Sci. and Tech. Rev., 4, 25 (2011). https://doi.org/10.25103/jestr.041.03.
  • A. Khorram, M. Ghoreishi, M.R.S. Yazdi and M. Moradi. Engg., 3, 708 (2011). https://doi.org/10.4236/eng.2011.37084.
  • S. Rajakumar, C. Muralidharan and V. Balasubramanian. Proc. of the Instn. of Mech. Engs. Part B: J. of Engg. Manuf., 224, 1175 (2010). https://doi.org/10.1243/09544054JEM1802.
  • A. Vairis and M. Petousis. J. of Engg. Sci. and Tech. Rev., 2, 99 (2009). https://doi.org/10.25103/jestr.021.19.
  • K.Y. Benyounis and A.G. Olabi. J. Ad. in Engg., 39, 483 (2008). https://doi.org/10.1016/j.advengsoft.2007.03.012.
  • K. Maji, D.K. Pratihar and K. Nath. The Int. J. of Adv. Manufg Tech., 83, 1441 (2016). https://doi.org/10.1007/s00170-0157675-0.
  • S.L. Chen and D. Shen. The Int. J. of Adv. Manufg Tech., 15, 70 (1999). https://doi.org/10.1007/s001700050041.
  • R. Li, Y. Jin, Z. Li and K. Qi. J. of Mats. Engg. and Perf., 23, 3085 (2014). https://doi.org/10.1007/s11665-014-1146-x.
  • S. Liu and R. Kovacevic. The Int. J. of Adv. Manufg Tech., 74, 867 (2014). https://doi.org/10.1007/s00170-014-6041-y.
  • Y. Zhao, Y. Zhang, W. Hu and X. Lai. Opt. and Las. in Engg., 50, 1267 (2012). https://doi.org/10.1016/j.optlaseng.2012.03.010.
  • A. Al-Ahmari, M. Ashfaq, A. Alfaify, B. Abdo, A. Alomar and D. Dawud. J. of Mech. Sci. and Tech., 30, 345 (2016). https://doi.org/10.1007/s12206-015-1239-y.
  • W. Guo, D. Crowther, J.A. Francis, A. Thompson and L. Li., The Int. J. of Adv. Manufg Techy, 84, 2547 (2016). https://doi.org/10.1007/s00170-015-7881-9.
  • N.N. Korra, M. Vasudevan and K.R. Balasubramanian, The Int. J.of Adv. Manufg Tech., 77, 67 (2015). https://doi.org/10.1007/s00170-014-6426-y.
  • L. Romoli and C.A.A. Rashed. The Int. J. of Adv. Manufg Techy., 81(1), 563 (2015). https://doi.org/10.1007/s00170015-7234-8.
  • A.H. Plaine, A.R. Gonzalez, U.F.H. Suhuddin, J.F. dos Santos and N.G. Alcântar. The Int. J. of Adv. Manufg Tech., 85, 1575 (2016). https://doi.org/10.1007/s00170-015-8055-5.
  • K. Manonmani, N. Murugan and G. Buvanasekaran. The Int. J. of Adv.Manufg. Tech., 32, 1125 (2007). https://doi.org/10.1007/s00170-006-0432-7.
  • A. Mostafapour and S. Davoodi. Transactions of the Indian Inst. of Metals., 69, 1129 (2016). https://doi.org/10.1007/s12666-015-0675-9.
  • D.C. Montgomery. Statistical Quality Control, Sixth Ed. John Wiley and Sons Inc, New York, USA, (2009).
  • J.S. Milton and Jesse C. Arnold. Introduction of Probability and Statistics, Fourth Ed. McGraw-Hill, Europe, (2002).
  • S.R. Schmidt and R.G. Launsby. Understanding Industrial Designed Experiments, Fourth Ed. Air Academy Press, Colorado, USA, (1994).
  • C.R. Hicks. Fundamental Concepts in the Design of Experiments, Fifth Ed. Oxford University Press. New York, USA, (1999).
  • G.E.P. Box and K.B. Wilson. J. Roy. Statist. Soc. Ser. B Metho., 13, 1 (1951).
  • D.C. Montgomery. Design and Analysis of Experiments, Second Ed. John Wiley and Sons, New York, USA, 2007.
  • G.E.P. Box and D.W. Behnken. Technometrics, 2, 455 (1960). https://doi.org/10.1080/00401706.1960.10489912.
  • D.C. Montgomery. Design and Analysis of Experiments, Eighth Ed. John Wiley & Sons Inc, New York, USA, (2013).

Abstract Views: 270

PDF Views: 0




  • Application of Response Surface Methodology for Modeling of Laser Transformation Hardening of Commercially Pure Titanium ASTM Grade3

Abstract Views: 270  |  PDF Views: 0

Authors

Duradundi Sawant Badkar
School of Mechanical Engineering, Dr. A. D. Shinde Institute of Technology, Guddai, Bhadgaon − 416502, Gadhinglaj, Kolhapur, Maharashtra, India

Abstract


In the presented study, the laser transformation hardening of commercially pure titanium sheet material of thickness being 1.6mm is investigated using CW, 1.6 kW solid State Nd: YAG laser. A Full Factorial Design (FFD) with Response Surface Methodology (RSM) is employed to establish, optimize and to investigate the relationships of three laser transformation hardening process parameters such as laser power, scanning speed, and focused position on laser hardened bead profile parameters such as hardened bead width, hardened depth, heat input and power density. In this work, Laser Transformation Hardening (LTH) with high precision and an optimum desired minimum value of hardened depth of 241 microns has been accomplished with heat input = 150 J/cm and power density = 294.08 W/mm2 for the laser process parameters of lower beam power: 750 Watts, high scanning speed: 3000 mm/min and a defocused beam of –30 mm. Effects of laser process parameters on laser hardened bead geometries were carried out using RSM. Results indicate that the scanning speed has a positive effect on all hardened bead dimensions while the laser power has a positive effect particularly on hardened bead width as compared to hardened depth and heat input. The optimum laser hardening conditions are identified sequentially to minimise hardened depth, heat input, power density and maximum hardened bead width. The validation results demonstrate that the developed models are accurate with low percentages of error.

Keywords


Analysis of Variance, Bead Geometry, Full Factorial Design, Laser Transformation Hardening, Response Surface Methodology.

References





DOI: https://doi.org/10.18311/jsst%2F2019%2F18088