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theses

Additive manufacturing (AM) is a set of processes that build a three-dimensional part by additively joining raw material in a layer-by-layer fashion. This layer-by-layer approach inherently results in a ‘staircase’, which is prominently observed on the surface of the printed part giving rise to surface roughness. To obtain high quality 3D printed part, post-process finishing techniques are required that adds to high cost and production time. It is a high priority to obtain high-quality parts with minimum post-processing to reduce printing cost and time. In this work, we investigate the effect of printing process parameters on the resulting surface profile through numerical simulation in order to improve surface quality of the printed part. We use Projection Micro Stereolithography (PμSL) as a model AM process.
A mathematical model based on photopolymerization principle is established to simulate 3D printing environment. This model will produce a layer profile computationally, which is equivalent to experimentally printed layer profile. The shape of the layer is dependent on various printing parameters, including resin constituents such as photo-initiator and photo-absorber, process parameters such as layer thickness and curing time, and environmental factors such as oxygen concentration. The objective of this work is to optimize the process parameters for fabricating high surface quality structures. Varying these parameters will affect the shape of layer and, as a result, surface roughness of the structure as well. Based on the simulated layer profile, a stacked layer structure is generated computationally, from which a simulated surface profile is extracted. This is compared to the experimentally obtained value from a printed part.
Based on Taguchi Design of Experiment method, the number of simulations to be performed is reduced from 35 to 27 simulations to achieve minimum surface roughness obtainable within the given range of printing parameter space. The optimized parameters are used to print high quality structures for two different cases. First, vertical micro-struts are printed with optimum parameters and compared with the result obtained with nominal parameters. The result shows that the optimized parameters reduce surface roughness by 40%. Second, simulated micro-struts with an inclination angle are studied as surface roughness increases with decrease in inclination angle. With the optimized parameters, the simulation shows that surface roughness of the inclined strut decreases by 45% on left edge and 34% on right edge compared to the part with nominal parameters.
In conclusion, surface topography of a vertical or inclined 3D printed strut can be improved by optimizing the print process parameters using the mathematical model and Taguchi method, and high-quality parts can be manufactured with reduced post-processing cost and time.

ETD_9253

doi:10.7282/T3G73JB3

M.S.

Includes bibliographical references

by Ishan Mukund Bhalerao

ETD graduate

The author owns the copyright to this work.