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Background Despite computer‐aided design and computer‐aided manufacturing (CAD/CAM) technology improving prosthesis fit, errors inherent to digital workflow still exist. Purpose To measure scanning/milling errors, and identify factors influencing marginal (MD) and internal discrepancy (ID). Materials and Methods After scanning, 22 conical abutments in 5 master casts, 6 suprastructures with more than 2 implants (3, 4, and 6) were CAD designed. Angular deviation and errors in the vertical/horizontal planes were analyzed using a coordinate measuring machine (CMM). CAD suprastructures were milled and MD/ID evaluated with micro‐computed tomography (CT) and optic microscopy (OM) at one screw test (OST) and final fit test (FFT). Results Mean scanning errors, at the vertical/horizontal planes, and angulation error were 3 μm ± 13, 44 μm ± 34, 0.3° ± 0.2°, respectively. Angulation errors nearly double in structures >3 abutments (0.26°vs 0.4°). OM MD in FFT/OST was 57.7 μm ± 13.9/100.7 μm ± 34.6, respectively. Micro‐CT FFT‐MD was 38.9 μm ± 12.8. Lineal/perimetral ID was 49.6 μm ± 11.9 and 108.2° ± 41.8, respectively. Structures >3‐implants were 2.3 times more likely to present higher MD (CI95%:0.4‐13.6). Nearly all the internal horizontal gap was due to scanning errors (44 of 49.6 μm). Horizontal scanning errors were three times more likely to present greater ID (CI95%:0.5‐17.4). Conclusion Horizontal plane scanning errors are greater than vertical errors. Scanning angulation/milling errors are higher for suprastructures>3implants. Scanning/milling errors are associated with ID/MD, respectively, leading to micro‐gap formation. A CMM reduces scanning errors in >3‐implant‐frameworks before milling the final piece.

Gas metal arc welding (GMAW) is one of the most used joining method in the industry.However, one of the main problems of this process is the generation of residual stresses which have direct impact on the fatigue life of welded components. Nevertheless, residual stress pattern prediction is complex and requires the simulation of the welding process. Currently, there are different numerical methods to predict the residual stresses generated in GMAW process, being Goldak's method one of the most widely used model. However, the main limitation of these methods is that they require defining many parameters experimentally and consequently this method is not valid during design process.Alternatively, in this work, it is developed a procedure where the heat source is defined based on the welding physics for spray transfer welding. The developed procedure has been validated for a spray transfer multipass butt weld case. Results have shown good correspondence with an average deviation of 9.16% in thermal field and 42 MPa in the final residual stress field. Thus, the developed procedure has been validated as a cost effective alternative method to estimate residual stress pattern in spray transfer multipass welding. Furthermore, the developed method does not require any welding experimental characterization once the efficiency of the used welding machine is defined. The proposed method can be used as a valid tool to optimize the welding process in order to minimize the residual stress field and, consequently, improve the fatigue life.

Universities are one of the fundamental actors to guarantee the dissemination of knowledge and the development of competences related to the Industry of the Future (IoF) or Industry 4.0. Computer Aided (CAX) and Product Lifecycle Management (PLM) technologies are key part in the IoF. With this aim, it was launch a project focused on Manufacturing and partially funded by La Fondation Dassault Systèmes. This communication presents a review on CAX-PLM training, four initiatives already in place in universities participating in the project, the project scope, the approach to integrate with the industrial context, the working method to consider different competence profiles and the development framework.