| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Ribeiro, João
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (8/8 displayed)
- 2023Solidification and heat-treatment conditions affecting the tensile properties and fracture feature of an automotive alsimg alloycitations
- 2023Failure analysis of biocomposite sandwich pipe under internal pressure-Application for high pressure gas transportation pipelines MEDGAZcitations
- 2023Flow Visualizations in a PDMS Cerebral Aneurysm Biomodel
- 2021Parametric optimization of the GMAW welding process in thin thickness of austenitic stainless steel by Taguchi methodcitations
- 2017Optimization of cutting parameters to minimize the surface roughness in the end milling process using the Taguchi methodcitations
- 2011The Contour Method for Residual Stress Determination Applied to an AA6082-T6 Friction Stir Butt Weldcitations
- 2011Moire Interferometry Assessement of Residual Stress Variation in Depth on a Shot Peened Surfacecitations
- 2009Measurement of Residual Stresses with Optical Techniquescitations
Places of action
| Organizations | Location | People |
|---|
article
Optimization of cutting parameters to minimize the surface roughness in the end milling process using the Taguchi method
Abstract
This paper presents a study of the Taguchi design application to optimize surface quality in a CNC end milling operation. The present study includes feed per tooth, cutting speed and radial depth of cut as control factors. An orthogonal array of L9 was used and the ANOVA analyses were carried out to identify the significant factors affecting the surface roughness. The optimal cutting combination was determined by seeking the best surface roughness (response) and signal-to-noise ratio. The study was carried-out by machining a hardened steel block (steel 1.2738) with tungsten carbide coated tools. The results led to the minimum of arithmetic mean surface roughness of 1.662 μm, being the radial depth of cut the most infuent parameter, with 64% of contribution for the workpiece surface fnishing.