Optimization of the cyclone separator performance using taguchi method and multi-response pcr-topsis

Authors

  • Arifin Zulkarnain Mechanical Engineering Department, Akademi Teknik Soroako
  • Abbas Hammada Mechanical Engineering Department, Hasanuddin University
  • Fauzan Fauzan Mechanical Engineering Department, Hasanuddin University

DOI:

https://doi.org/10.12928/ijio.v3i1.4272

Keywords:

Taguchi, pcr, TOPSIS, CFD, Helical

Abstract

Pollutant control uses cyclone separators as pre-cleaners and is widely used in manufacturing and mining industries. Research on cyclone performance is carried out with changes in various variations that affect it, the problem that occurs is that multi-response can give results of different factors and levels as a result of equipment design cannot provide optimal results and research topics on inlet scroll types have not been widely carried out, this study aims to improve cyclone performance inlet scroll type separator with helical angle, experimental and development methods to get optimal performance where pressure drop and efficiency are indications of cyclone separator performance, to get optimal performance the use of Taguchi experimental design produces different factors and levels so that multi-response methods such as PCR and TOPSIS was used to produce the best combination of factors and levels, confirmation experiments and computational fluid dynamics (CFD) methods were carried out to ensure the validity of the study, the results showed that the scroll inlet prototype cyclone separator with a helical angle of 150, inlet velocity of 10m/s, outlet diameter of 72 mm provides empirical values ​​for pressure drop and the best particle separation efficiency for multi-parameter responses, further research can be done by modifying the shape and dimensions of the bottom outlet.

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Published

2022-06-03

How to Cite

Zulkarnain, A., Hammada, A. . ., & Fauzan, F. . (2022). Optimization of the cyclone separator performance using taguchi method and multi-response pcr-topsis. International Journal of Industrial Optimization, 3(1), 33–46. https://doi.org/10.12928/ijio.v3i1.4272

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