Application of Hooke & Jeeves Algorithm in Optimizing Fusion Zone Grain Size and Hardness of Pulsed Current Micro Plasma Arc Welded AISI 304L Sheets

Abstract

AISI 304L is an austenitic Chromium-Nickel stainless steel offering the optimum combination of corrosion resistance, strength and ductility. These attributes make it a favorite for many mechanical components. The paper focuses on developing mathematical models to predict grain size and hardness of pulsed current micro plasma arc welded AISI 304L joints. Four factors, five level, central composite rotatable design matrix is used to optimize the number of experiments. The mathematical models have been developed by Response Surface Method (RSM) and its adequacy is checked by Analysis of Variance (ANOVA) technique. By using the developed mathematical models, grain size and hardness of the weld joints can be predicted with 99% confidence level. The developed mathematical models have been optimized using Hooke and Jeeves algorithm to minimize grain size and maximize the hardness.

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K. Prasad, C. Rao and D. Rao, "Application of Hooke & Jeeves Algorithm in Optimizing Fusion Zone Grain Size and Hardness of Pulsed Current Micro Plasma Arc Welded AISI 304L Sheets," Journal of Minerals and Materials Characterization and Engineering, Vol. 11 No. 9, 2012, pp. 869-875. doi: 10.4236/jmmce.2012.119081.

Conflicts of Interest

The authors declare no conflicts of interest.

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