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Full-Text Articles in Engineering
Prediction Of Meltpool Depth In Laser Powder Bed Fusion Using In-Process Sensor Data, Part-Level Thermal Simulations, And Machine Learning, Grant King
Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research
The goal of this thesis is the prevention of flaw formation in laser powder bed fusion additive manufacturing process. As a step towards this goal, the objective of this work is to predict meltpool depth as a function of in-process sensor data, part-level thermal simulations, and machine learning. As motivated in NASA's Marshall Space Flight Center specification 3716, prediction of meltpool depth is important because: (1) it can serve as a surrogate to estimate process status without the need for expensive post-process characterization, and (2) the meltpool depth provides an avenue for rapid qualification of microstructure evolution. To achieve the …
Minimax Registration For Point Cloud Alignment, Zhaohui Geng, Mauro Garcia, Bopaya Bidanda
Minimax Registration For Point Cloud Alignment, Zhaohui Geng, Mauro Garcia, Bopaya Bidanda
Manufacturing & Industrial Engineering Faculty Publications and Presentations
The alignment, or rigid registration, of three-dimensional (3D) point clouds plays an important role in many applications, such as robotics and computer vision. Recently, with the improvement in high precision and automated 3D scanners, the registration algorithm has become critical in a manufacturing setting for tolerance analysis, quality inspection, or reverse engineering purposes. Most of the currently developed registration algorithms focus on aligning the point clouds by minimizing the average squared deviations. However, in manufacturing practices, especially those involving the assembly of multiple parts, an envelope principle is widely used, which is based on minimax criteria. Our present work …
Grey-Taguchi Approach To Optimize Fused Deposition Modeling Process In Terms Of Mechanical Properties And Dimensional Accuracy, Md Asif Bin Syed, Qausar Rhaman, Hasan Md Shahriar, Mohammad Muhshin Aziz Khan
Grey-Taguchi Approach To Optimize Fused Deposition Modeling Process In Terms Of Mechanical Properties And Dimensional Accuracy, Md Asif Bin Syed, Qausar Rhaman, Hasan Md Shahriar, Mohammad Muhshin Aziz Khan
Graduate Student Scholarship
Fused Deposition Modeling (FDM) is a process that allows for the rapid production of functional parts through the deposition of fused material layers in a sequential manner. FDM has flexibility and the potential to create complicated parts. This study aims to optimize the FDM process parameters in terms of tensile strength, flexural strength, and longitudinal shrinkage using the Grey-Taguchi approach. The input parameters chosen to study the effects on dimension and mechanical properties are layer thickness, the raster angle, fill density, the number of contours, printing temperature, and printing speed. The Taguchi L27 orthogonal array is used as the statistical …
Workforce Development Strategies In Additive Manufacturing, Mel Cossette, Ismail Fidan, Gaffar Gailani, Angran Xiao
Workforce Development Strategies In Additive Manufacturing, Mel Cossette, Ismail Fidan, Gaffar Gailani, Angran Xiao
Publications and Research
Additive Manufacturing (AM), also known as 3D Printing (3DP), is one of the newest manufacturing technologies with growing utilization in our daily life. Parallel to this growth, new materials, machines, and specific processes are being developed to produce parts in better-finished quality, at lower cost, and with shorter production time. However, workforce education in this evolving field has not advanced at the same pace as the technology, lacking proven curriculums, high-quality/accredited degree programs, and specialized advanced degrees. In this paper, some best practices established by the authors are introduced. The list is far from exhaustive but is proven to be …