ABSTRACT
Today, three-dimensional scanners allow to reconstruct an oral cavity in a virtual environment, with advantages in the design of dental prostheses and in the automation of product cycles related to dentistry. Currently, data acquisition can be performed by means of intra-oral or extra-oral scanning devices. The first ones allow to directly obtain the prepared tooth geometry, but the scanned surface must be dried and sprayed with powder to avoid light reflection. Intra-oral digitization is also affected by the real clinical condition, such as saliva, blood or movement of the patient. Thus, the indirect procedure with impression taking and model production is still more accurate and the stone replica is commonly digitized (DeLong et al. 2003). From the virtual model of the prepared tooth, a technician designs the prosthesis using specific CAD programs. The availability of the
mathematical model allows to produce the dental device by Computer Aided Manufacturing (CAM) tools or Rapid Prototyping (RP) processes. CAM techniques are already quite popular on the market, but the real innovation, enabled by the recent introduction of new biocompatible materials in the RP, is the direct production (Rapid Manufacturing, RM) of dental metal devices for final application. Since the quality of the product is crucial for the success of the patient treatment, it becomes essential to define a methodology for evaluating the production stages. Dimensional errors are certainly produced by the digitization and surface reconstruction processes, but they can be evaluated, thus becoming controllable. Other errors, not controllable, are induced by each step of the manufacturing sequence from the CAD model of the replica to the final cap. Therefore, it becomes important to investigate new technologies to quantify their accuracy and precision. Currently, there is not a standard methodology for evaluating the error introduced by each step of the manufacturing cycle, from the scanning of the replica to the final dental device. To have comparable data, a standard benchmark must be employed.
