F. Bettine, H. Ameddah, and R. Manaa, “
A NEURAL NETWORK APPROACH FOR PREDICTING KINEMATIC ERRORS SOLUTIONS FOR TROCHOIDAL MACHINING,”
International Journal of Modern Manufacturing Technologies, vol. x, no. 1, 2018.
Publisher's VersionAbstract
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.
F. Bettine, H. Ameddah, and R. Manaa, “
A neural network approach for predicting kinematic errors solutions for trochoidal machining in the matsuura MX-330 Five-axis Machine,”
FME Transactions , vol. 46, no. 4, pp. 453-462, 2018.
Publisher's VersionAbstract
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.
K. Chergui, H. Ameddah, and H. Mazouz, “
Biomechanical Analysis of Fatigue Behavior of a Fully Composite-based Designed Hip Resurfacing Prosthesis,”
Journal of the Serbian Society for Computational Mechanics, vol. 12, no. 2, pp. 80-94, 2018.
Publisher's VersionAbstract
The Hip resurfacing prosthesis is subjected to different stresses resulting from the different positions of the human walk, thereby generating dynamic stresses that vary with time, leading the implant material to fatigue failure. It is important to study the fatigue behavior of the prosthesis material and to ensure its long lifetime. We proposed a new composite material named CF/PA12 composed of carbon fibers with a polyamide 12 resin, whose biocompatibility had been demonstrated in laboratories. In this study, we investigated the static and dynamic behavior at different Gait cycle positions of a Hip resurfacing prosthesis entirely made of new CF/PA12 composite. A fatigue behavior will be deducted by a Finite Element Analysis using the commercial SolidWorks software compatible with the Abaqus finite element code. Static and dynamic analysis were conducted considering normal walking and climbing stairs loading at different Gait cycle percentages of 2, 13, 19, 50 and 63%. The results obtained showed that Hip resurfacing prosthesis fully made of new CF/PA12 composite was very far from fatigue and therefore from failure.
M. Amadji, H. Ameddah, and H. Mazouz, “
Numerical Shape Optimization of Cervical Spine Disc Prosthesis Prodisc-C,”
Journal of Biomimetics, Biomaterials and Biomedical Engineering, vol. 36, pp. 56-69, 2018.
Publisher's VersionAbstract
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.