Mechanical Property Characterization of a 3D Printing Manufacturing System

Additive manufacturing is making it possible to increase the complexity of designed mechanical structures. However, the variability inherent to this manufacturing process can influence significantly the performance of structural elements, specially in phononic crystals and metamaterials since their working principles relies on the repetition of identical cells with a dedicated designed geometry. In this work, first, a design of experiments approach is applied to a determine a sampling strategy in order to characterize an additive manufacturing machine. Then, mechanical properties of the samples are inferred using material properties measured with an ultrasound transducer. The material density was measured using the weight of the samples, both dry and immersed in water, using the buoyancy force expression. It is known that the elastic modulus measured via ultrasound is biased. Therefore, the distributions inferred using ultrasound measurements were updated using experimental forced responses of sample rods and dynamic models via the Spectral Element Model. Updated values are used in statistical regression modeling to infer the stochastic field over print are of the 3D printer. The presented work is a first step in the longer term research goal: to show how to model the overall variability of a given additive manufacturing process, which is usually obtained in the statistical process control, and explain how to use it in the design of robust phononic crystal and metamaterial designs. The printing direction presented a statistically significant relationship with the elastic modulus and with the mass density, while only the printing direction presented a statistically significant relationship for the shear modulus.