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Digital Twins In Advanced Manufacturing To Enhance Manufacturing Efficiency, Max Kirkpatrick
Digital Twins In Advanced Manufacturing To Enhance Manufacturing Efficiency, Max Kirkpatrick
Theses and Dissertations
Digital Twins of manufacturing systems are an emerging tool for improvement, optimization, and monitoring of physical manufacturing systems. The idea of representing physical systems with digital depictions has been prevalent since the early days of Computer Aided Design (CAD), but recently the concept of a Digital Twin has been expanded to encapsulate more than just a digital model of a design. Instead, the Digital Twin offers a unique, comprehensive, and real-time toolset for analysis and improvement of physical systems. These tools can be used to improve system efficiency, perform “what-if” analyses, virtually commission manufacturing equipment, analyze system performance in real …
Use Of Dic Measurements With Finite Element Models For Direct Heterogeneous Material Property Determination And Wrinkle Formation During Automated Fiber Placement, Sreehari Rajan Kattil
Use Of Dic Measurements With Finite Element Models For Direct Heterogeneous Material Property Determination And Wrinkle Formation During Automated Fiber Placement, Sreehari Rajan Kattil
Theses and Dissertations
In this work, application of DIC in combination with finite element modeling is demonstrated for efficient material characterization for complex heterogeneous materials and tow wrinkle formation during automated fiber placement.
The first part of the work describes the integration of DIC measurements with finite element models for direct property identification in heterogeneous material systems. The material property identification is based on solving partial differential equations (PDE) of equilibrium for unknown elastic material properties with known boundary conditions and full field strain data (Eg. DIC). The PDEs are solved numerically using Petrov-Galerkin finite element procedure. The classical Bubnov-Galerkin method is shown …
Hybrid Theory-Machine Learning Methods For The Prediction Of Afp Layup Quality, Christopher M. Sacco
Hybrid Theory-Machine Learning Methods For The Prediction Of Afp Layup Quality, Christopher M. Sacco
Theses and Dissertations
The advanced manufacturing capabilities provided through the automated fiber placement (AFP) system has allowed for faster layup time and more consistent production across a number of different geometries. This contributes to the modern production of large composite structures and the widespread adaptation of composites in industry in general and aerospace in particular. However, the automation introduced in this process increases the difficulty of quality assurance efforts. Industry available tools for predicting layup quality are either limited in scope, or have extremely high computational overhead. With the advent of automated inspection systems, direct capture of semantic inspection data, and therefore complete …