Optimization of CNC Turning Parameters Using Taguchi Method

Authors

  • Rifelino Rifelino Department of Mechanical, Faculty of Engineering, Universitas Negeri Padang, Padang 25131, Indonesia
  • Bulkia Rahim Department of Mechanical, Faculty of Engineering, Universitas Negeri Padang, Padang 25131, Indonesia
  • Eko Indrawan Department of Mechanical, Faculty of Engineering, Universitas Negeri Padang, Padang 25131, Indonesia

DOI:

https://doi.org/10.24036/teknomekanik.v4i1.11072

Keywords:

Optimization, Surface Roughness, Taguchi Method, CNC Turning

Abstract

The surface roughness quality of machining product plays important role when it contacted with other machine components. That quality depends on several parameters setting, such as material, cutting tool, cutting condition and operator skill. The aim of this study is to obtain the optimum setting of turning parameters by using Taguchi method. Three control factors: cutting speed, depth of cut, and feeding at three different levels are selected. A series CNC turning process on AISI 1045 material were performed using L9 (3)3 orthogonal array with cutting fluid. Insert carbide cutting tool is used in the experiment. In order to reveal the optimum machining parameter, smaller the better is quality characteristic selected for surface roughness examination of workpiece. Analysis of experiment results revealed that higher cutting speed, low feed, low depth of cut respectively, provides fine surface quality of machined workpiece. Moreover, feed f parameter was found most influence to the surface rougness quality with 53.73% contribution, cutting speed v provides 23.28% contribution, and depth of cut a provides 17.87% contribution. Confirmation experiment shows that level 3 of cutting speed, level 2 of cutting depth, and level 1 of feed deliver smoothest machined surface of Ra 0,46 µm.

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References

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Published

2021-05-28

How to Cite

Rifelino, R., Rahim, B., & Indrawan, E. (2021). Optimization of CNC Turning Parameters Using Taguchi Method. Teknomekanik, 4(1), 42–48. https://doi.org/10.24036/teknomekanik.v4i1.11072

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Section

Research Articles