Next Article in Journal
Rebar Corrosion Investigation in Rubber Aggregate Concrete via the Chloride Electro-Accelerated Test
Next Article in Special Issue
Intelligent Optimization of Hard-Turning Parameters Using Evolutionary Algorithms for Smart Manufacturing
Previous Article in Journal
Hybrid Superconducting-Ferromagnetic [Bi2Sr2(Ca,Y)2Cu3O10]0.99(La2/3Ba1/3MnO3)0.01 Composite Thick Films
Previous Article in Special Issue
Multiscale 3D Curvature Analysis of Processed Surface Textures of Aluminum Alloy 6061 T6
Article Menu

Export Article

Open AccessArticle
Materials 2019, 12(6), 860; https://doi.org/10.3390/ma12060860

Optimal Machining Strategy Selection in Ball-End Milling of Hardened Steels for Injection Molds

1
Universitat Politècnica de Catalunya (UPC)-Escola Tècnica Superior d’Enginyeria Industrial de Barcelona (ETSEIB), 08034 Barcelona, Spain
2
Universidad Pública de Navarra-Dpto. de Ingeniería, 31006 Navarra, Spain
*
Author to whom correspondence should be addressed.
Received: 12 February 2019 / Revised: 8 March 2019 / Accepted: 8 March 2019 / Published: 14 March 2019
Full-Text   |   PDF [3017 KB, uploaded 14 March 2019]   |  

Abstract

In the present study, the groups of cutting conditions that minimize surface roughness and its variability are determined, in ball-end milling operations. Design of experiments is used to define experimental tests performed. Semi-cylindrical specimens are employed in order to study surfaces with different slopes. Roughness was measured at different slopes, corresponding to inclination angles of 15°, 45°, 75°, 90°, 105°, 135° and 165° for both climb and conventional milling. By means of regression analysis, second order models are obtained for average roughness Ra and total height of profile Rt for both climb and conventional milling. Considered variables were axial depth of cut ap, radial depth of cut ae, feed per tooth fz, cutting speed vc, and inclination angle Ang. The parameter ae was the most significant parameter for both Ra and Rt in regression models. Artificial neural networks (ANN) are used to obtain models for both Ra and Rt as a function of the same variables. ANN models provided high correlation values. Finally, the optimal machining strategy is selected from the experimental results of both average and standard deviation of roughness. As a general trend, climb milling is recommended in descendant trajectories and conventional milling is recommended in ascendant trajectories. This study will allow the selection of appropriate cutting conditions and machining strategies in the ball-end milling process. View Full-Text
Keywords: surface finish; high speed milling (HSM); roughness; modeling surface finish; high speed milling (HSM); roughness; modeling
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Buj-Corral, I.; Ortiz-Marzo, J.-A.; Costa-Herrero, L.; Vivancos-Calvet, J.; Luis-Pérez, C. Optimal Machining Strategy Selection in Ball-End Milling of Hardened Steels for Injection Molds. Materials 2019, 12, 860.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Materials EISSN 1996-1944 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top