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—An iterative search process of Metaheuristic to efficiently determine the optimum depends on the parameter levels. There are various natural intelligences and inspirations and in this work, Elephant Herding Optimisation algorithm or EHO was selected to find maximal solutions of some noisy non-linear and multimodal continuous mathematical functions. Metaheuristics with their own benefits are then merged with the conventional response surface methods. An aim is to avoid the design point to be premature during the refinement of the process variables in the context of response surface methodology. The new electrostatic process is automatically used for aluminium coating on metallic alloy wheels. It is very difficult to make powder coating run under various influential process variables, resulting in significantly lower customer specification for appearance issues. This study focuses on the optimisation of electrostatic powder coating process variable level via the novel elephant herding optimisation algorithm on the modified simplex method with multiple performance measures. The experimental results suggest that the proposed levels of process variables from the proposed method seems to be more efficient on the multiple response surfaces when compared with the previous operating condition. In addition, two phases based on the response surface methodology was also applied to study the EHO parameter levels via some performance measures.
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