Application of Response Surface Methodolody to Prediction of Dilution in Plasma Transferred Arc Hardfacing of Stainless Steel on Carbon Steel

  • V. BalasubramanianEmail author
  • A. K. Lakshminarayanan
  • R. Varahamoorthy
  • S. Babu


The application of response surface methodology was highlighted to predict and optimize the percentage of dilution of iron-based hardfaced surface produced by the PTA (plasma transferred arc welding) process. The experiments were conducted based on five-factor five-level central composite rotatable design with full replication technique and a mathematical model was developed using response surface methodology. Furthermore, the response surface methodology was also used to optimize the process parameters that yielded the lowest percentage of dilution.

Key words

plasma transferred arc hardfacing dilution response surface methodology 


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  1. [1]
    Budinski Kenneth G. Surface Engineering for Wear Resistance [M]. New York, Prentice-Hall Inc, 1988.Google Scholar
  2. [2]
    Wu Weite, Wu Lung-Tien. The Wear Behavior Between Hard-facing Materials [J]. Metallurgical and Materials Transactions, 1996, 27A(11): 3639.CrossRefGoogle Scholar
  3. [3]
    Kumar S, Mondal D P, Khaira H K, et al. Improvement in High Stress Abrasive Wear Property of Steel by Hardfacing [J]. Journal of Materials Engineering and Performance, 1999, 8(6): 711.CrossRefGoogle Scholar
  4. [4]
    Nadkarni S V. Modern Arc Welding Technology [M]. New Delhi: Oxford and IBH Publishing Co Pvt Ltd, 1996.Google Scholar
  5. [5]
    Gatto A, Bassoli E, Fornari M. Plasma Transferred Arc Deposition of Powdered High Performances Alloys: Process Parameters Optimization as a Function of Alloy and Geometrical Configuration [J]. Surface and Coatings Technology, 2004, 187(2–3): 265.CrossRefGoogle Scholar
  6. [6]
    d’Oliveira A S C M, Vilar R, Feder C G. High Temperature Behaviour of Plasma Transferred Arc and Laser Co-Based Alloy Coatings [J]. Applied Surface Science, 2002, 201(30): 154.CrossRefGoogle Scholar
  7. [7]
    Gurumoorthy K. Microstructural Aspects of Plasma Transferred Arc Surfaced Ni-Based Hardfacing Alloy [J]. Materials Science and Engineering, 2007, 456(15): 11.CrossRefGoogle Scholar
  8. [8]
    Grainger S. Engineering Coatings—Design and Application [M]. 1st ed. Cambridge: Abington Publishing, 1989.Google Scholar
  9. [9]
    Subramaniam S, White D R, Jones J E, et al. Experimental Approach to Selection of Pulsing Parameters in Pulsed GMAW [J]. Welding Journal, 1999, 78(5): 166s.Google Scholar
  10. [10]
    Allen T T, Richardson R W, Tagliabue D P, et al. Statistical Process Design for Robotic GMA Welding of Sheet Metal [J]. Welding Journal, 2002, 81(5): 69s.Google Scholar
  11. [11]
    Murugan N, Parmer R S. Stainless Steel Cladding Deposited by Automatic Gas Metal Arc Welding [J]. Welding Journal, 1997, 76(10): 391s.Google Scholar
  12. [12]
    Marimuthu K, Murugan N. Prediction and Optimization of Weld Bead Geometry of PTA Hardfaced Valve Seat Rings [J]. Surface Engineering, 2003, 19(1): 143.CrossRefGoogle Scholar
  13. [13]
    Bourithis L, Papadimitriou G D. Synthesizing a Class “M” High Speed Steel on the Surface of a Plain Steel Using the Plasma Transferred Arc (PTA) Alloying Technique: Micro-structure and Wear Properties [J]. Materials Science and Engineering, 2003, A361(1–2): 165.CrossRefGoogle Scholar
  14. [14]
    Balasubramanian V, Varahamoorthy R, Ramachandran C S, et al. Selection of Welding Process for Hardfacing on Carbon Steels Based on Quantitative and Qualitative Factors [J]. The International Journal of Advanced Manufacturing Technology, 10. 1007/s00170-008-1406-8.Google Scholar
  15. [15]
    Gunaraj V, Murugan N. Application of Response Surface Methodology for Predicting Weld Bead Quality in Submerged Arc Welding of Pipes [J] Journal of Materials Processing Technology, 1999, 88(1): 266.CrossRefGoogle Scholar
  16. [16]
    Montgomery D C. Design and Analysis of Experiments [M]. New York, John Wiley and Sons, 1991.zbMATHGoogle Scholar
  17. [17]
    Miller I, Freund J E, Johnson. Probability and Statistics for Engineers [M]. New Delhi: Prentice of Hall of India Pvt Ltd, 1999.zbMATHGoogle Scholar
  18. [18]
    Lin Bor-Tsuen, Jean Ming-Der, Chou Jyh-Homg. Using Response Surface Methodology for Optimizing Deposited Partially Stabilized Zirconia in Plasma Spraying [J]. Applied Surface Science, 2007, 253(6): 3254.CrossRefGoogle Scholar
  19. [19]
    Benyounis K Y, Olabi A G. Optimization of Different Welding Processes Using Statistical and Numerical Approaches—A Reference Guide [J]. Advances in Engineering Software, 2008, 39(6): 483.CrossRefGoogle Scholar
  20. [20]
    Montgomery D C. Design and Analysis of Experiments 3 [M]. New York, John Wiley, 2001.Google Scholar
  21. [21]
    Kumar S, Kumar P, Shan H S. Effect of Evaporative Casting Process Parameters on the Surface Roughness of Al-7% Si Alloy Castings [J]. Material Processing Technology, 2007, 182 (1): 615.CrossRefGoogle Scholar
  22. [22]
    Öktem H, Erzurumlu T, Kurtaran H. Application of Response Surface Methodology in the Optimization of Cutting Conditions for Surface Roughness [J]. Journal of Materials Processing Technology, 2005, 170(1–2): 11.CrossRefGoogle Scholar
  23. [23]
    Tien Chuen-Lin, Lin Shane-Wen. Optimization of Process Parameters of Titanium Dioxide Films by Response Surfaces Methodology [J]. Optics Communications, 2006, 266(2): 574.CrossRefGoogle Scholar

Copyright information

© China Iron and Steel Research Institute Group 2009

Authors and Affiliations

  • V. Balasubramanian
    • 1
    Email author
  • A. K. Lakshminarayanan
    • 1
  • R. Varahamoorthy
    • 1
  • S. Babu
    • 1
  1. 1.Centre for Materials Joining and Research (CEMAJOR), Department of Manufacturing EngineeringAnnamalai UniversityAnnamalai NagarIndia

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