Quality edge extraction of mechanical CAD parts for intelligent manufacturing

Computer aided testing (CAT) is the latest technique. It is because CAT involve in a different stages of manufacturing like designing, production and quality control by 3D measuring instrument that is time consuming. If the object position is known before examined, time can be managed. Machine vision dependent inspection of mechanical CAD parts has become demanding area in the field of industrial inspection. In this work, we developed the procedure to detect the mechanical CAD parts with the edge-based algorithms. The data has been taken with 3D model that has been designed using solid edge ST8 CAD/CAM PLM software and analysed using MATLAB for automated production checking system. Our proposed method uses the edge-based recognition of CAD object by fuzzy-based approach in order to create image information of shape before it can be used for pose estimation in computer aided testing system. From the experimental results, it has been found that with the proposed vision system more accurate and reliable products can be manufactured intelligently.