On the Hardfacing Performance Optimization after Plasma Transfer Arc Experiments

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Abstract:

The paper describes response surface methodology (RSM) based on design of experiments and analysis of variance (ANOVA) as a statistical design while developing a robust plasma transfer arc (PTA)coating process. Based on ANOVA, The relative important parameters with respect to surface at hardness values were identified in the Taguchi design, where they were further used in predictors. In addition, we applied three-dimensional graphs in RSM to develop a robust PTA response surface yielding the desired-better area of a treated layer. In this study, a quadratic polynomial with a Box-Behnken design is utilized. The results reveal that RSM provides the effective methods as compared to the traditional trial-and-error method for exploring the effects of controlled factors on response. A very good agreement was observed, as evidenced by R-squared value, 90%, between the predicted and the experimental data, and its error percent is found to be approximately 3.801% in the PTA-coating process. It is clear that RSM model demonstrated better accuracy in predicting surface hardness for PTA-coating process. Accordingly, RSM based on design of experiments was used as statistical PTA-coating design tools combined with the hardness model. Device zone optimization and yield enhancement have been demonstrated.

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Periodical:

Advanced Materials Research (Volumes 189-193)

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3640-3646

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February 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] Sharples, R.V., The Plasma Transferred Arc Weld Surfacing Process, the Welding Institute, USA, (1985).

Google Scholar

[2] Jeffus, L., Welding: Principles and Applications, Fourth Edition, International Thomson Publishing Inc, (1999).

Google Scholar

[3] Su, Y.L., and Chen, K.Y., Wear, 209 (1997) 160-170.

Google Scholar

[4] Frederiksson, H., and Savage, S., Rapidly Quenched Materials, Amsterdam, New York, (1991) 156-206.

Google Scholar

[5] Edrisy, A., and Alpas, A.T., Thin Solid Films, 420–421, (2002) 338–344.

DOI: 10.1016/s0040-6090(02)00937-9

Google Scholar

[6] Rabiei, A., Mumm, D.R., Hutchinson, J.W., Schweinfest, R., Ru¨ hle, M., and Evans, A.G., Materials Science and Engineering, A269 (1999) 152–165.

Google Scholar

[7] Chazelas, C., Coudert, J.F., Jarrige, J., and Fauchais, P., Journal of the European Ceramic Society, 26 (2006) 3499–3507.

DOI: 10.1016/j.jeurceramsoc.2006.01.018

Google Scholar

[8] Wu, C.S. and Gao, J.Q., Computational Materials Science, 24 (2002) 323–327.

Google Scholar

[9] Kerstena, H., Deutsch, H., Steffen, H., Kroesen, G.M.W., and Hippler, R., Vacuum, 63 (2001) 385–431.

Google Scholar

[10] Ranjit, K.R., A Primer on The Taguchi Method , Van Nostrand Reihold, USA, (1990) 45-73.

Google Scholar

[11] Montgomery, D. C., Design and Analysis of Experiments, John Wiley &Sons, (2003) 13-35(14).

Google Scholar

[12] Myers, R. H., and. Montgomery, D.C., Response surface methodology: Process and product optimization using design experiments, John-Wiley & Sons, USA, (1995).

Google Scholar

[13] Vijaya, M., Krishna, R., Prabhakar, O., and Shankar, N.G., Surface and Coatings Technology, 79 (1996) 276-288.

Google Scholar

[14] Chen, Y., Wang, G., and Zhang, H., Thin Solid Films, 390 (2001) 13-19.

Google Scholar

[15] Wachter, R., and Cordery, A., Diamond and Related Materials, 6 (1997) 537-541.

Google Scholar