Publications

2018
Ameddah, Hacene, and Hammoudi Mazouz. 2018. “IN VIVO CHARACTERIZATION OF MICRO ARCHITECTURE OF A HUMAN VERTEBRA BY MICRO-IMAGING”. 6th International Conference Integrity-Reliability-Failure 22-26 July. Publisher's Version Abstract
Bone, like any other material, is subject to mechanical fatigue when subjected to repetitive cyclic loading. Cyclic loading in vivo occurs either in workplaces exposed to mechanical vibration or during handling operations or during leisure and sports activities. As an example, the continuous exposure of the human body to intense global vibration can be, in the long run, cause problems of lumbar lesions due to dynamic stresses (mainly compression) in the spine. Bone and microcracks in cancellous bone. Fatigue rupture of vertebral bone is clinically and biologically important. From a clinical point of view, permanent damage and deformity, under cyclic loading, can probably weaken the vertebral body by inducing the migration of joint replacements. The mechanism of fatigue damage in cortical and trabecular bone can cause cracks and their propagation to final rupture. Microcracks observed in the vertebrae contributed to the decrease in vertebral rupture strength. In order to analyze the biomechanical behavior of the vertebrae and to assess the risk of fracture, an in vivo characterization method is applied based on the micro-MRI, aiming to focus on the evaluation the force at rupture of the vertebral body in compression. The method of extracting the shape of cancellous bone by special filters (adaptive filter, Robert’s filter, etc.) will be applied, allowing it to be modelled as a slice (2D). This micro slice are created by edge configuration generation and triangulated cube configuration generation in capturing section contour points from medical image per slice, creating B-spline curve with the control points in each layer, producing solid model construction in Planar Contours method. Medical rapid prototyping models are performed in SolidWorks. Layered manufacturing techniques are used for producing parts of arbitrary complexity, which will then be modelled by finite element in fatigue.
The prediction of machining accuracy of a Five-axis Machine tool is a vital process in precision manufacturing. This work presents a novel approach for predicting kinematic errors solutions in five axis Machine. This approach is based on Artificial Neural Network (ANN) for trochoidal milling machining strategy. We proposed a multi-layer perceptron (MLP) model to find the inverse kinematics solution for a Five-axis Machine Matsuura MX-330. The data sets for the neural-network model is obtained using Matsuura MX-330 kinematics software. The solution of each neural network is estimated using inverse kinematics equation of the Machine tool to select the best one. As a result, the Neural Network implementation improves the performance of the learning process. In this work trochoidal trajectory generation formulation has been developed and simulated using the software Matlab Inc. The main advantage of the trochoidal path is to present a continuous path radius leading the machining process to take place under favorable conditions (no impact, less marking of the part, ...). Obtaining the toolpath is to allow programming of the toolpath according to ISO 6983 (which defines the principles of the G code). For this, numerical study of trochoidal strategy and experimental result are presented with aims to full milling and to ensure a control of radial engagement.
Bettine, Farida, Hacene Ameddah, and Rabah Manaa. 2018. “A NEURAL NETWORK APPROACH FOR PREDICTING KINEMATIC ERRORS SOLUTIONS FOR TROCHOIDAL MACHINING”. International Journal of Modern Manufacturing Technologies x (1). Publisher's Version Abstract
The prediction of machining accuracy of a fiveaxis machine tool is a vital process in precision manufacturing for machining a hard and free form surfaces. This work presents a novel approach for predicting kinematic errors solutions in five-axis machine for trochoidal milling strategy. This approach is based on Artificial Neural Network (ANN) for trochoidal milling machining strategy. We proposed a multi-layer perceptron (MLP) model to find the inverse kinematics solution for a five-axis machine. The data sets for the neural-network model are obtained using kinematics software. The solution of each neural network is estimated using inverse kinematics equation of the machine tool to select the best one. As a result, the Neural Network implementation improves the performance of the learning process. For this, numerical study of trochoidal strategy and experimental results are presented with aims to full milling and to ensure a control of radial engagement. The experimental result shows the efficiency of the method by obtainning the toolpath and the machining possebility of this new type of strategy emerging.
Amadji, Moussa, Hacene Ameddah, and Hammoudi Mazouz. 2018. “Numerical Shape Optimization of Cervical Spine Disc Prosthesis Prodisc-C”. Journal of Biomimetics, Biomaterials and Biomedical Engineering 36 : 56-69. Publisher's Version Abstract
Various ball and socket-type designs of cervical artificial discs are in use or under investigation. All these disc designs claim to restore the normal kinematics of the cervical spine. In this study, we are interested in the cervical prosthesis, which concerns the most sensitive part of the human body, given the movements generated by the head. The goal of this work is to minimize the constraints by numerical shape optimization in the prodisc-C cervical spine prosthesis in order to improve performance and bio-functionality as well as patient relief. Prodisc-C cervical spine prosthesis consists of two cobalt chromium alloy plates and a fixed nucleus. Ultra-high molecular weight polyethylene, on each plate there is a keel to stabilize the prosthesis; this prosthesis allows thee degrees of freedom in rotation. To achieve this goal, a static study was carried out to determine the constraint concentrations on the different components of the prosthesis. Based on the biomechanical behaviour of the spine discs, we totally fixed the lower metal plate; a vertical load of 73.6 N to simulate the weight of the head was applied to the superior metallic endplate. After a static study on this prosthesis, using a finite element model, we noticed that the concentration of the Von-Mises stress is concentrated on the peripheral edge core and the concave articulating surface of the superior metallic endplate the numerical. We use the module optimization for 3D SolidWorks for optimize our design, based on the criteria of minimizing stress value. Shape optimization concluded to minimize the equivalent stress value on both joint surface (concave and convex) from 11.3 MPa to 9.1MPa corresponding to a percentage decrease of 19.4% from the original geometry. We conclude that despite the fact that maximum Von Mises stresses are higher in the case of the dynamic load, remains that they are weak. Which is an advantage for the durability of the prosthesis and-also for the bone, because a low stress concentration on the prosthesis will reduce stress concentration generated by the implant on the bone, therefore its risk of fracture reduces.
Abdennour, BENDAIKHA, and BENAMAR Bilal. 2018. “Etude d'un convoyeur de bouteilles de l'unité ENAJUC N'Gaous”.
Ali, MAAMIR Sidi, and NOURI Hichem. 2018. “Etude d'une chaine de conditionnement de JUS COMBI Bloc”.
Cherifa, Azoui, and Benmohammed Brahim. 2018. “Stability lobes prediction in high speed milling , ISSN 2067–3604”. International Journal of Modern Manufacturing Technologies Vol. X (N°1) : pp 37-42. Publisher's Version Abstract
Different techniques are used to obtain approximate solutions for delayed functional differential equations (RFDEs). All these models used the so-called stability lobe diagrams, to choose the maximum axial depth of cut for a given spindle speed associated with a free chatter in machining. In this research paper, the ZOA (Zeroth Order Approximation) and SD (Semi Discretization) methods are explained, developed and used to obtain the stability lobe diagrams for a milling cutting system with two degree of freedom, in high speed machining case.
2017
Faiza, Khalid, et al. 2017. “Simulation du comportement thermomécanique d’une poutre sandwiche en matériaux composites”. 3ème Conférence Internationale de Mécanique ICM’2017 , 26-27/04/.
Houari, HABIB, and Benmansour Nabila. 2017. “Etude théorique de l'usure des outils de coupe reveus et non revetus”.
Abderraouf, Benali, and Benmohammed Brahim. 2017. “Prédiction des efforts de coupe pour le fraisage périphérique en utilisant la théorie prédictive d’Oxley et la loi de comportement de Johnson-Cook”. La 3ème Conférence Internationale de Mécanique (I.C.M.’ 2017) Annaba, 26-27 Avril . Publisher's Version

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