The dimensional and geometrical quality of additively manufactured parts must be increased to match industrial requirements before they can be incorporated to mass production. Such an objective has a great relevance in the case of features of linear size that are affected by dimensional or geometrical tolerances. This work proposes a design for additive manufacturing strategy that uses the re-parameterization of part design to minimize shape deviations from cylindrical geometries. An analysis of shape deviations in the frequency domain is used to define a re-parameterization strategy, imposing a bi-univocal correspondence between verification parameters and design parameters. Then, the significance of variations in the process and design factors upon part quality is analyzed using design of experiments to determine the appropriate extension for modelling form deviation. Finally, local deviations are mapped for design parameters, and a new part design including local compensations is obtained. This strategy has been evaluated upon glossy surfaces manufactured in a Vero™ material by polymer jetting. The results of the proposed example showed a relevant improvement in dimensional quality, as well as a reduction of geometrical deviations, outperforming the results obtained with a conventional scaling compensation.
Laser triangulation systems (LTS) are one of the most popular non-contact inspection techniques. These systems are widely used in reverse engineering tasks as they allow for a fast acquisition of thousands of points that represent the geometry of the part in a virtual 3D model. The accuracy and repeatability of these systems are lower than the traditional contact inspection techniques, as they depend on the surface properties, the illumination conditions and the LTS configuration. Present work deals with the influence of surface material on the quality of the virtual model. The objective is to evaluate the behaviour of different materials and their suitability for being digitized.
In order to compete with traditional manufacturing processes, Additive Manufacturing (AM) should be capable of producing medium to large batches at industrial-degree quality and competitive cost-per-unit. This paper proposes a systematic framework approach to the problem of fulfilling dimensional and geometric requirements for medium batch sizes of AM parts, which has been structured as a three-step optimization methodology. Firstly, specific work characteristics are analyzed so that information is arranged according to an Operation Space (factors that could have an influence upon quality) and a Verification Space (formed by quality indicators and requirements). Standard process configuration leads to characterization of the standard achievable quality. Secondly, controllable factors are analyzed to determine their relative influence upon quality indicators and the optimal process configuration. Thirdly, optimization of part dimensional and/or geometric definition at the design level is performed in order to improve part quality and meet quality requirements. To evaluate the usefulness of the proposed framework under quasi-industrial condition, a case study is presented here which is focused on the dimensional and geometric optimization of surgical-steel tibia resection guides manufactured by Laser-Power Bed Fusion (L-PBF). The results show that the proposed approach allows for part quality improvement to a degree that matches the initial requirements.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.