Accuracy control of complex surfaces in reverse engineering

CAD systems have greatly affected the way which engineers perform their function. Computers have simplified and eliminated many of repetitious tasks and the gap between computer models and physical products has significantly shortened. These tools have stimulated the impetus for product development but the manufacturing processes still depends on human skills which ultimately reduce errors and produce better products. Complex shapes representing the patient’s anatomy are widely applied, namely in computer-assisted surgery and manufacturing of customized implants. These type of models represent a challenge for the reverse engineering processes and are not comparable with the demands of regular geometric models. In order to create a replica, data is processed in a series of steps that transforms the initial data obtained from the physical model into a three dimensional digital model. Most commonly it is necessary to include filtering, segmentation, mesh smoothing and surface generation. These steps can strongly affect the accuracy of the model. It is therefore necessary to find a compromise between the finest accuracy and maximum deviation acceptable to reduce computer processing time and achieve the best model. This study shows an iterative and alternating process to produce more accurate complex geometry models.