@enit.rnu.tn
University of Tunis El Manar (UTM), National Engineering School of Tunis (ENIT), Laboratory of Applied Mechanics and Engineering (LMAI), Tunisia
National Engineering School of Tunis (ENIT)
Tarek Mabrouki is working as Professor (full) in Mechanical Engeneering at ENIT "National Engineering School of Tunis", member of the "University of Tunis El Manar".
Previously, he was Professor at "INSA de Lyon" for 12 years ago and a senior lecturer at ENSAM ParisTech, for 3 Years. He received his Ph.D degree from "Arts et Métiers ParisTech", Paris, France, in 2000. He also obtained the "Habilitation à Diriger des Recherches en sciences, abbreviated "HDR", which is a French diploma of "accreditation to supervise research", from both INSA de Lyon and University of Claude Bernard (Lyon 1). Tarek Mabrouki has received a M.S. degree (DEA) from "Université Pierre et Marie Curie" Paris VI, France, in 1996 and an Engineer Diploma (bac+6), from "Ecole Nationale d'Ingénieurs de Sfax" (ENIS), in 1995. His main research interests include the study of manufacturing processes: machining, Waterjet cutting, material forming, additive manufacturing, modelling and simulation.
Include modelling of coupled physical phenomena applied to the numerical simulation of manufacturing processes: machining, Waterjet cutting, material forming, additive manufacturing, modelling and simulation
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Boutheyna Gasmi, Mohamed Athmane Yallese, Septi Boucherit, Salim Chihaoui, and Tarek Mabrouki
SAGE Publications
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 L32 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.
Chaima Souaidi, Mohamed Athman Yallese, Abdelaziz Amirat, Salim Belhadi, and Tarek Mabrouki
Springer Science and Business Media LLC
Habib Zargayouna, Essaieb Hamdi, and Tarek Mabrouki
Springer Nature Switzerland
Thabet A. M. Sghaier, Habib Sahlaoui, Tarek Mabrouki, Haifa Sallem, and Joël Rech
Springer Nature Switzerland
Asma Belhadj, Salma Slama, Mouhamed Hichem Habouba, and Tarek Mabrouki
Springer Nature Switzerland
Thabet A. M. Sghaier, Habib Sahlaoui, Haifa Sallem, Tarek Mabrouki, and Joël Rech
Springer Nature Switzerland
Wahid Tarhouni, Hassen Khlifi, Lefi Abdellaoui, Mihed Ben Said, Tarek Mabrouki, and Wassila Bouzid Saï
Springer Nature Switzerland
Farooq Ahmed, Furqan Ahmad, Fethi Abbassi, S. Thirumalai Kumaran, and Tarek Mabrouki
Elsevier BV
Thabet A. M. Sghaier, Habib Sahlaoui, Tarek Mabrouki, Haifa Sallem, and Joël Rech
Springer Science and Business Media LLC
Wahid Tarhouni, Lefi Abdellaoui, Hassen Khlifi, Mihed Ben Said, Tarek Mabrouki, and Wassila Bouzid Sai
Springer Science and Business Media LLC
Imed Boughdiri, Tarek Mabrouki, Redouane Zitoune, Khaled Giasin, and Mohamed Faycal Ameur
Elsevier BV
Riadh Saidi, Tarek Mabrouki, Salim Belhadi, and Mohamed Athmane Yallese
Springer International Publishing
Muhammad Asad, Hassan Ijaz, Muhammad Azhar Ali Khan, Mushtaq Khan, Tarek Mabrouki, and Muhammad Usman Rashid
Elsevier BV
Khaoula Safi, Mohamed Athmane Yallese, Salim Belhadi, Tarek Mabrouki, and Salim Chihaoui
SAGE Publications
The present study examines the machining of a cold work tool steel (X210Cr12) using a triple chemical vapor deposition coated carbide tool (Al2O3/TiC/TiCN). The paper is focused on an experimental investigation as well as a modeling and optimization of the working cutting parameters in relationship with the studied material. For that, first, a set of experimental tests were built in order to evaluate the effect of cutting parameters (r, Vc, f, and ap) on the output parameters, namely surface roughness (Ra), cutting force (Fz), insert flank wear (Vb), and 3D roughness distribution. In a second step, a Taguchi L16 (4^3 2^1) design of experiment (DoE) was exploited with the aim to develop a modeling of output working parameters based on the response surface methodology. An optimization of the cutting conditions was performed using the desirability function (DF) approach and the hybrid Taguchi-weighted aggregate sum product assessment method. The desired objective is to obtain optimal cutting regime corresponding to the simultaneous minimization of parameters Ra and Fz, and maximization of material removal rate. The results found show that the factor f influences Ra with 42.55% and that parameter ap affects parameters Fz and Pc with 67.55 and 60.88%, respectively. For the DF and WASPAS methods, the optimal regimes selected is r = 1.6 mm, Vc = 366 m/min, ap = 0.17 mm, f = 0.16 mm/rev and r = 1.6 mm, Vc = 180 m/min, ap = 0.3 mm, and f = 0.08 mm/rev, respectively. The proposed work concerns all mechanical manufacturing companies, as it provides the necessary information on the optimal working conditions of the tool/material pair.
Khaoula Safi, Mohamed Athmane Yallese, Salim Belhadi, Tarek Mabrouki, and Aissa laouissi
Springer Science and Business Media LLC
Imed Boughdiri, Tarek Mabrouki, Redouane Zitoune, and Khaled Giasin
Springer International Publishing
Imed Boughdiri, Khaled Giasin, Tarek Mabrouki, and Redouane Zitoune
Elsevier BV
Septi Boucherit, Sofiane Berkani, Mohamed Athmane Yallese, Riad Khettabi, and Tarek Mabrouki
Periodica Polytechnica Budapest University of Technology and Economics
In the current paper, cutting parameters during turning of AISI 304 Austenitic Stainless Steel are studied and optimized using Response Surface Methodology (RSM) and the desirability approach. The cutting tool inserts used in this work were the CVD coated carbide. The cutting speed (vc), the feed rate (f) and the depth of cut (ap) were the main machining parameters considered in this study. The effects of these parameters on the surface roughness (Ra), cutting force (Fc), the specific cutting force (Kc), cutting power (Pc) and the Material Removal Rate (MRR) were analyzed by ANOVA analysis.The results showed that f is the most important parameter that influences Ra with a contribution of 89.69 %, while ap was identified as the most significant parameter (46.46%) influence the Fc followed by f (39.04%). Kc is more influenced by f (38.47%) followed by ap (16.43%) and Vc (7.89%). However, Pc is more influenced by Vc (39.32%) followed by ap (27.50%) and f (23.18%).The Quadratic mathematical models, obtained by the RSM, presenting the evolution of Ra, Fc, Kc and Pc based on (vc, f, and ap) were presented. A comparison between experimental and predicted values presents good agreements with the models found.Optimization of the machining parameters to achieve the maximum MRR and better Ra was carried out by a desirability function. The results showed that the optimal parameters for maximal MRR and best Ra were found as (vc = 350 m/min, f = 0.088 mm/rev, and ap = 0.9 mm).
Dorian Fabre, Cédric Bonnet, Tarek Mabrouki, and Joël Rech
SAGE Publications
Broaching operations require stiff machine tools that have to withstand high cutting forces. This work aims to develop a methodology to predict the macroscopic cutting forces on a real, internal broaching operation comprising a large number of teeth. The macroscopic forces are estimated, based on the addition of local forces that are applied to each section and are simultaneously in contact with the broach. These local forces are calculated using a model of specific cutting pressure, depending on the rise per tooth. This study uses two methods to identify this specific cutting pressure model, that is, a direct approach based on orthogonal cutting tests and an inverse approach based on an instrumented broaching operation. It is shown that the direct method is effective in identifying a specific cutting pressure model and enables the prediction of macroscopic forces. Moreover, the direct approach provides more comprehensive results in terms of radial forces.
Lassaad Kilani, Tarek Mabrouki, Mahfoudh Ayadi, Hechmi Chermiti, and Salim Belhadi
Springer Science and Business Media LLC
Muhammad Asad, Faramarz Djavanroodi, Hassan Ijaz, Muhammad Azhar Ali Khan, Muhammad Usman Rashid, and Tarek Mabrouki
World Scientific and Engineering Academy and Society (WSEAS)
A finite element based numerical model to simulate orthogonal machining process and associated burr formation process has been developed in the presented work. To incorporate simultaneous effects of mechanical and thermal loadings in high speed machining processes, Johnson and Cook`s thermo-visco-plastic flow stress model has been adopted in the conceived numerical model. A coupled damage-fracture energy approach has been used to observe damage evolution in workpiece and to serve as chip separation criterion. Simulation results concerning chip morphology, nodal temperatures, cutting forces and end (exit) burr have been recorded. Model has been validated by comparing chip morphology and cutting force results with experimental findings in the published literature. Effects of cutting edge geometries [Hone and Chamfer (T-land)] on burr formation have been investigated thoroughly and discussed in length. To propose optimum tool edge geometries for reduced burr formation in machining of an aerospace grade aluminum alloy AA2024, numerical analyses considering multiple combinations of cutting speed (two variations), feed (two variations) and tool edge geometries [Hone edge (two variations), Chamfer edge (four variations)] have been performed. For chamfer cutting edge, the “chamfer length” has been identified as the most influential macro geometrical parameter in enhancing the burr formation. Conversely, “chamfer angle” variation has been found least effecting the burr generation phenomenon.