Session: ASME Undergraduate Student Design Expo

Paper Number: 164885

Mechanical Properties of Additively Manufactured Parts Through Infill Density and Raster Angle Variation 

Additive Manufacturing (AM) is a fabrication technique that creates parts layer by layer, which has gained popularity due to its ability to reduce material waste. However, the layer-by-layer process results in parts with anisotropic properties, meaning their mechanical characteristics vary depending on the direction of the layers. This anisotropic behavior is influenced by several factors, including the printing parameters and printing directions used during manufacturing. A key challenge in AM is predicting the mechanical behavior of printed parts, as this can significantly affect their performance in real-world applications. This research aims to enhance the understanding of the mechanical behavior of additively manufactured parts, specifically focusing on how printing parameters such as infill density and raster angle affect performance. Infill density is the percentage of a part’s internal volume filled with material during printing, directly impacting material usage and part strength. The raster angle represents the direction in which the infill is printed, which also influences the strength and stiffness of the part. Mechanical test samples were produced using material extrusion, an AM process where material is dispensed through a nozzle along predefined paths. These parts were subjected to tensile testing following ASTM standards using an 800 Series Universal Tensile Tester by Test Resources. During testing, two main parameters were varied: infill density and raster angle. Infill densities of 25%, 50%, 75%, and 100% were tested, while raster angles of 0°-90°, 30°-60°, and 45°-45° were used. Preliminary results indicated that increasing the infill density resulted in higher values for both Young's Modulus and Ultimate Tensile Strength, suggesting that denser parts are stronger and stiffer. Among the raster angles, the 45°-45° configuration produced the highest mechanical performance for both Young’s Modulus and Ultimate Tensile Strength. These findings suggest that an optimal combination of high infill density and the right raster angle could improve mechanical properties in AM parts. Alongside physical testing, computer-aided engineering (CAE) simulations were performed using nTopology to assess the behavior of AM parts under various conditions. The simulations were compared with experimental data to evaluate their accuracy. Initial results showed good agreement with physical test results, but discrepancies were observed at lower infill densities (below 100%). These findings highlight the need for improved computational models to better predict the anisotropic behavior of AM parts. This research aims to develop more accurate models for predicting the mechanical properties of AM parts, providing engineers with valuable tools to optimize designs before manufacturing. By better understanding the relationship between infill density, raster angle, and mechanical properties, AM parts can be more effectively optimized for specific applications, improving the efficiency and reliability of the manufacturing process.

Presenting Author: Matthew Azaroff Kennesaw State University

Presenting Author Biography: My name is Matthew Azaroff, I am an undergraduate student attending Kennesaw State University (KSU), currently in the last semester of my Bachelor of Science in Mechanical Engineering Technology Degree. I have an interest in nuclear additive materials because of my passion for additive manufacturing. My future goal is to begin my Ph.D. in Interdisciplinary Engineering with a concentration in Innovative Materials. Presently, I plan to work this summer with Idaho National Laboratory on implementing metal additive manufacturing technologies at Kennesaw State University.

Authors:

Matthew Azaroff Kennesaw State University
Samantha Bevis Kennesaw State University
Edgar Bryant Kennesaw State University
Mechack Nduwa Kennesaw State University
Aaron Adams Kennesaw State University
David Stollberg Kennesaw State University