Session: 14-02: Applications and Reliability of Sensors

Paper Number: 146882

146882 - Digital Twin Model for Property Assessment of Metal Additive Manufacturing 

Additive manufacturing (AM) has revolutionized the manufacturing industry by offering flexibility, customization, and rapid prototyping capabilities. Complex geometries and low volume parts can be produced via AM in much lower lead time and cost compared to traditional manufacturing methods such as forging, casting and machining. However, ensuring the quality and reliability of AM parts remains a significant challenge due to variations in material properties and process parameters. In addition, despite the traditional manufacturing techniques where the quality assessment processes have been established over the years, standardization of quality inspection methods for AM is still a challenge. Traditional material property analysis methods, that require experimental testing and computational modeling, are often costly and time-consuming and often not applicable to the complex geometries of AM components. These challenges are further magnified when repetitive sampling is required. To address these challenges, this paper presents a novel approach that combines experimental findings with Finite Element Modeling (FEM) to construct a digital twin (DT) model of AM parts. The DT model will serve as a virtual representation along with real-time monitoring, simulation, and optimization capabilities. By creating a digital twin model, manufacturers can simulate various scenarios and conditions, allowing them to optimize processes and predict performance outcomes before implementation. In this study, the digital twin model is developed using COMSOL Multiphysics, a finite element analysis software. The CAD model of the sample, same as the model which is used for 3D printing of the parts in a laser powder bed fusion process, is imported into COMSOL in .STL file format, and adjustments are made to align with physical samples tested via Resonant Ultrasound Spectroscopy (RUS), micro-mechanical material testing to identify the elasticity of the parts and machining processes post-printing. The automated mesh generation in COMSOL, utilizing the physics-controlled mesh option, streamlines the process of creating the digital twin model. Numerical simulations are conducted to correlate the resonance frequency of parts at different process conditions with their material characteristics, represented as RF Z-score values. The correlation is plotted and shows clear isolation and separation of different sample groups based on their RF Z-score values and other material properties. Additional material characterization testing including tensile, fatigue and nondestructive testing of the samples have been conducted as the supplementary experiments and for comparison of the results for different manufacturing processing conditions. Hence, the results suggest that such an approach provides manufacturers with cost-effective and efficient means of analyzing material properties and optimizing AM processes Moreover, by leveraging digital twin technology, manufacturers can achieve greater process control and quality assurance in additive manufacturing. The findings of this study contribute to advancing the understanding and implementation of digital twin technology in AM; therefore, paving the way for enhanced productivity and reliability in additive manufacturing processes.

Presenting Author: Poojith Chowdary Chigurupati Georgia Southern University

Presenting Author Biography: I'm Poojith Chowdary Chigurupati a Graduate Student at Georgia Southern University, Statesboro. Also, a research assistant in LANDTIE lab and my interests are mostly in Additive Manufacturing and NDT. I have a bachelor's degree from mechanical and currently pursuing my master's degree in advanced Additive manufacturing major.

Authors:

Malik Marks Georgia Southern University
Poojith Chowdary Chigurupati Georgia Southern University
Hossein Taheri Georgia Southern University