The use of robot end-effectors programmed to perform handling tasks in industrial environments has expanded in several sectors as a consequence of the rapid digital transformation seen in recent years. With such growing demands, additive manufacturing is evolving in the robotics field with more efficient, innovative, and customer-specific solutions owing to its design flexibility. Thus, this work presents a robot end-effector developed and produced by powder bed fusion (PBF) to execute palletizing operations in the automotive electronics industry, where electrostatic discharge interference is a critical concern. To guarantee the functionality of the developed robot end-effector under real conditions of implementation, prototypes of polyamide 12 (PA12) and PA12 incorporating graphene nanoplatelets were fabricated and characterized. This included the assessment of the mass, electrical surface resistance, and mechanical properties under tensile and compressive loads using biaxial strain gauges coupled to the prototypes for local strain monitoring. The experimental data were then used to define multilinear isotropic hardening models needed to numerically characterize the robotic system. At last, the final product was validated in an industrial environment at Bosch Car Multimedia S.A. Through the applied methodology, valuable insights in guiding process parameters optimization and materials selection for functional PBF parts depending on the technical requirements demanded by industrials are provided.

To ensure dimensional repeatability of additively manufactured parts, it is crucial to evaluate their dimensional and geometrical properties and to determine the capabilities of these systems to produce certain features. In this sense, the purpose of this research is to understand the influence of the layer thickness on the dimensional and geometrical accuracy of parts produced by powder bed fusion–laser beam. Three builds of a standard test artefact were fabricated in AlSi10Mg with three different layer thicknesses: 0.025 mm, 0.050 mm, and 0.075 mm. Some features including pins, holes, and staircase flats of various sizes were measured using computed tomography and an inspection software. The results showed that relative dimensional errors tend to be higher in smaller features, regardless of the layer thickness. Moreover, in some features, a higher layer thickness provided less dimensional deviations although with superior surface roughness. Regardless of the feature type, the minimum size achieved was 0.5 mm, with tolerances in the 5 ≤ IT ≤ 11 range, which applies to parts with mechanical constraints, medium finishing, and potential use in functional parts. Based on these findings, this research showed that it is possible to save around 60% of the build time for AlSi10Mg parts, depending on the dimensional, geometrical, and surface roughness requirements for each application.

Powder-bed fusion (PBF) additive manufacturing technologies have the potential to produce near-net shaped complex final parts for various industries, such as aerospace and automotive