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
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.
In this paper, an interactive application tool has been developed for creating 3D models of anatomical organs and other body structures from 2D medical imaging data. 3D models are generated by using reverse engineering algorithm and Planar Contour method by SolidWorks developed in Visual Basic Language. The research includes transferring Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) images into digital matrixes, entering digital matrixes into SolidWorks environment, building feature library for 3D reconstruction, creating medical rapid prototyping models. 3D reconstruction is 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. The results of this paper are to develop image processing 3D visualization in SolidWorks Application Programming Interface (API) using Visual Basic Language. The results reveal that the accuracy of 3D reconstruction is acceptable.
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