Volume 8, No. 5, September 2019

General Information

  • ISSN: 2278-0149 (Online)
  • Abbreviated Title:  Int. J. Mech. Eng. Robot. Res.  
  • Editor-in-Chief: ​Prof Richard (Chunhui) Yang, Western Sydney University, Australia
  • Associate Editor: Prof. B.V. Appa Rao, Andhra University; Prof. Ian R. McAndrew, Capitol Technology University, USA
  • Managing Editor: Murali Krishna. B
  • DOI: 10.18178/ijmerr
  • Abstracting/Indexing: Scopus (since 2016), CNKI, Google Scholar, Crossref, etc.
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International Journal of Mechanical Engineering and Robotics Research
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Variable Tuning for Electrostatic Powder Coating Process via Elephant Herding Optimisation Algorithm on Modified Simplex Method

Pongchanun Luangpaiboon
Industrial Statistics and operational Research Unit (ISO-RU), Department of Industrial Engineering, Faculty of Engineering, Thammasat University, Pathumthani, 12120 Thailand

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. 

Index Terms—electrostatic powder coating process, elephant herding optimisation algorithm, modified simplex method, noisy multimodal response surfaces, desirability function

Cite: Pongchanun Luangpaiboon, "Variable Tuning for Electrostatic Powder Coating Process via Elephant Herding Optimisation Algorithm on Modified Simplex Method" International Journal of Mechanical Engineering and Robotics Research, Vol. 8, No. 5, pp. 807-812, September 2019. DOI: 10.18178/ijmerr.8.5.807-812