Surface Roughness Optimization of some Machining Parameters in Turning Operations Using Taguchi Method
| Periodical | Advanced Materials Research (Volumes 62 - 64) |
|---|---|
| Main Theme | Advances in Materials and Systems Technologies II |
| Edited by | A.O. Akii Ibhadode, I.A. Igbafe and B.U. Anyata |
| Pages | 613-620 |
| DOI | 10.4028/www.scientific.net/AMR.62-64.613 |
| Citation | Ishaya Musa Dagwa, 2009, Advanced Materials Research, 62-64, 613 |
| Online since | February, 2009 |
| Authors | Ishaya Musa Dagwa |
| Keywords | Analysis of Variance (ANOVA), Machining Parameters, Signal-to-Noise Ratio (SNR), Surface Roughness Optimization, Taguchi Design Method |
| Price | US$ 28,- |
In this study, an attempt has been made to optimize cutting parameters (cutting speed, depth of cut, and feed rate) in conventional turning operations. A Taguchi orthogonal array (L933) was used in surface roughness optimization of a solid round bar of mild steel material. The experimental runs were randomized; two skilled machinists were involved in the turning operation using the same machining parameters. ANOVA analysis was performed to identify the percentage contribution of the factors affecting surface roughness during machining. The optimal cutting combination was determined by using the signal-to-noise ratio and the following results were obtained; speed (level 2) = 55.m/min, depth of cut (level 3) = 0.08mm, and feed rate (levels 3) = at 0.08mm/rev. A prediction of surface roughness was carried out using the optimal setting followed by a confirmatory test on the lathe. The result shows that the confirmatory runs compared favourably (96.44%) with the predicted surface roughness.
