The diffusion of Digital Additive Manufacturing technologies is leading to new needs by industrial research and development sectors. For instance mating additive manufactured parts is not a simple task, due to low accuracy typical of several additive technologies, such as Fused Deposition Modeling. Several papers report studies on how Fused Deposition Modeling accuracy is affected by process parameters. One of the most important aspects is the role of shrinkage during the transition from a semi-liquid state to solid and cooling at solid state. To avoid this drawback a Shrinkage Compensation Factor (SCF), an operator-controlled variable that affects the overall accuracy of the product, is embedded in the control software of FDM machines. In this paper the authors report a study on the influence of working parameters on FDM dimensional accuracy, focusing their attention on the validity of the Shrinkage Compensation Factor, especially when applied to cave parts and proposing a method to improve the accuracy of parts.

In the literature several papers report studies on mathematical models used to describe facial features and to predict female facial beauty based on 3D human face data. Many authors have proposed the Principal Component Analysis method that permits modeling of the entire human face using a limited number of parameters. In some cases, these models have been correlated with beauty classifications obtaining good attractiveness predictability using wrapped 2D or 3D models. To verify these results, in this paper the authors conducted a three-dimensional digitization study of 66 very attractive female subjects using a computerized non-invasive tool known as 3D digital photogrammetry. The sample consisted of the 64 contestants of the final phase of the Miss Italy 2010 beauty contest, plus the two highest ranked contestants in the 2009 competition. Principal Component Analysis (PCA) was conducted on this real faces sample to verify if there is a correlation between ranking and the principal components of the face models. There was no correlation and therefore this hypothesis is not confirmed for our sample. Considering that the results of the contest are not only solely a function of facial attractiveness, but undoubtedly are significantly impacted by it, the authors based on their experience and real faces conclude that PCA analysis is not a valid prediction tool for attractiveness. The database of the features belonging to the sample analyzed are downloadable online and further contributions are welcome.

In the last years close-range photogrammetric scanning systems, are acquiring a larger market share. This is due to low-cost hardware, components and to new user-friendly software. The ultimate, photogrammetric 3D scanning systems are very accurate and precise because, of the high-resolution cameras (over 10 Mpixels) they are equipped of and, the more precise algorithms of their software. The calibration phase is the primary step for the development of a, precise photogrammetric scanner. Through a good calibration it is indeed, possible to eliminate optical aberration issues and to obtain precise and, accurate three-dimensional measurements. In this study a powerful, calibration method, named full-field calibration, was implemented to, obtain high-precision values, using an original three-dimensional, calibrator, developed so as to increase the performance of this type of, calibration. Prior to using any measurement or 3D scanning system, precision and, accuracy have to be assessed. In this study a robust validation method, for photogrammetric scanning systems has been proposed. The validation, procedure consisted in: (1) operator error analysis, (2) reproducibility, error-analysis, (3) control-system error analysis, (4) scanning system, error analysis., The measurements taken using the "control system" (certified equipment in, terms of precision and accuracy) were considered as "gold standard". The, photogrammetric measurements, subsequently obtained by the scanning, system, were aligned to the "gold standard" using Procrustes, registration. The system error was expressed as the displacement between, these two sets of measurements.

Objectives: To define an acquisition protocol that is clear, precise, repeatable, simple and fast, and that is useful for analysis of the anthropometric characteristics of the soft tissue of the face. Materials and Methods: The analysis was carried out according to a new clinical-instrumental protocol that comprises four distinct phases: 1) set up of the portable equipment in the space in which the field analysis will be performed, 2) preparation of the subject, spatial positioning, 3) scanning of the subject with different facial expressions, 4) treatment and processing of the data. The protocol was tested on a sample comprised 66 female subjects (64 Caucasian, one Ethiopian, one Brazilian) who were the finalists in an Italian national beauty contest in 2010. To illustrate the potential of the method, we report here on the measurements and the full analysis that was carried out on the facial model of one of the subjects who was scanned. Results: This new protocol for the acquisition of faces is shown to be fast (phase 1 of about 1 h; phase 2, about 1.5 min; phase 3, about 1.5 min; phase 4, about 15 min), simple (phases 1-3 requiring a short operator training period; only phase 4 requires expert operators), repeatable (with direct palpation of the anatomical landmarks and marking of their positions on the face, the problem of identification of these same landmarks on the digital model is solved), reliable and precise (average precision of measurements, 0.5-0.6 mm over the entire surface of the face). Conclusions: This standardization allows the mapping of the subjects to be carried out following the same conditions in a reliable and fast process for all of the subjects scanned.