Professor of Mechanical Engineering and Smart Structures, School of Computing Engineering and Mathematics, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract—The statistical formulas are capable tools to find a regression of corrosion rate effectively among combining factors. One type of statistical model which is response surface methodology (RSM) has shown a proven method in minimizing number of running. Through this technique, this research study predicting corrosion rate of carbon steel as effects of pH, CO2 pressure and temperature. It can be used to run 3 dependent factors, 3 level experiment with only 16 number of running. The result reveals that NORSOK corrosion prediction software with second order model regression has 98 % of coefficient determination. Model prediction of Cassandra has 99.3% of coefficient determination. Second order model also has been verified with experimental data which shows a good correlation.
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