| 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 |
|
Mabrouki, Tarek
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (22/22 displayed)
- 2024Analysis of the Effect of Substituting Cement With Marble Powder on the Mortar Characteristics Used in 3D Printing
- 2023Selective laser melting of stainless-steel ::a review of process, microstructure, mechanical properties and post-processing treatmentscitations
- 2023Experimental study of morphological defects generated by SLM on 17-4PH stainless steel
- 2023Experimental investigation on the performance of ceramics and CBN cutting materials during dry machining of cast iron: Modeling and optimization study using RSM, ANN, and GAcitations
- 2023Mechanical properties of additively manufactured 17-4PH SS ::heat treatmentcitations
- 2020Modeling and Optimization of Cutting Parameters during Machining of Austenitic Stainless Steel AISI304 Using RSM and Desirability Approachcitations
- 2019Textile composite structural analysis taking into account the forming processcitations
- 2018Estimation and optimization of flank wear and tool lifespan in finish turning of AISI 304 stainless steel using desirability function approachcitations
- 2017Finite Element Analysis of Bend Test of Sandwich Structures Using Strain Energy Based Homogenization Methodcitations
- 2017Predictive modeling and multi-response optimization of technological parameters in turning of Polyoxymethylene polymer (POM C) using RSM and desirability functioncitations
- 2017Quality-productivity decision making when turning of Inconel 718 aerospace alloy: A response surface methodology approachcitations
- 2017Load transfer of graphene/carbon nanotube/polyethylene hybrid nanocomposite by molecular dynamics simulation
- 2016Performance of coated and uncoated mixed ceramic tools in hard turning processcitations
- 2015Mathematical modeling for turning on AISI 420 stainless steel using surface response methodologycitations
- 2015Modeling and optimization of tool wear and surface roughness in turning of austenitic stainless steel using response surface methodology
- 2015A new procedure to increase the orthogonal cutting machining time simulatedcitations
- 2014Load transfer of graphene/carbon nanotube/polyethylene hybrid nanocomposite by molecular dynamics simulations
- 2014Load transfer of graphene/carbon nanotube/polyethylene hybrid nanocomposite by molecular dynamics simulationcitations
- 2014RMS-based optimisation of surface roughness when turning AISI 420 stainless steelcitations
- 2013Three-dimensional finite element modeling of rough to finish down-cut milling of an aluminum alloycitations
- 2012Cutting simulation capabilities based on crystal plasticity theory and discrete cohesive elementscitations
- 2011Application of response surface methodology for determining cutting force model in turning hardened AISI H11 hot work tool steelcitations
Places of action
| Organizations | Location | People |
|---|
article
Experimental investigation on the performance of ceramics and CBN cutting materials during dry machining of cast iron: Modeling and optimization study using RSM, ANN, and GA
Abstract
<jats:p> This study focuses on the performance evaluation of CBN and ceramic tools in dry machining of gray cast iron EN GJL-350. The machining factors taken into account during turning are: cutting speed ( Vc), feed rate ( f), depth of cut ( ap), and cutting tool material (CBN, white ceramic, mixed ceramic, and silicon nitride). The first part of this investigation concerns the evaluation of the four cutting materials performance used in terms of tool wear evolutions, 2D and 3D surface roughness and cutting forces variation according to working parameters. The second part exposes the results according to L<jats:sub>32</jats:sub> Taguchi design of experiment. Statistical treatment by ANOVA allowed to quantify the impact of the input factors on the performance parameters, namely the surface roughness ( Ra), the cutting force ( Fz), the cutting power ( Pc), and the specific cutting energy ( Ecs). The response surface methodology (RSM), and the artificial neural network (ANN) approach were adopted to develop mathematical models for predicting the different output parameters. The results of the two methods were compared and discussed. A multi-criteria optimization was performed using the desirability function (DF) approach. The genetic algorithm (GA) was also applied to find pareto fronts. The results found show that CBN is the most efficient material in terms of lower tool wear, surface roughness and cutting forces. The DF method allowed to find an optimal combination ( Vc = 660 m/min, f = 0.13 mm/rev, ap = 0.232 mm, and the CBN material) leading to a compromise between the minimization of ( Ra, Fz, Pc, and Ecs) and the maximization of (MRR). The Pareto fronts found by the (GA) method make it possible to propose a multitude of solutions according to the desired objectives. </jats:p>