This thesis involves the development of digital algorithms for the microstructural analysis of metallic deposits produced through the use of Scanning Laser Epitaxy (SLE). SLE is a new direct digital manufacturing (DDM) technique which allows for the creation of three dimensional nickel-based superalloy components using an incremental layering system. Using a bed of powder placed on an underlying substrate and a laser propagating a melt-pool across the sample, a layer of material can be added and through the careful control of SLE settings various microstructures can be created or extended from the substrate. To create parts that are within specified microstructure tolerances the ideal SLE settings must be located through experimental runs, with each material needing different operating parameters. This thesis focuses on improving the microstructural analysis by use of a program that tracks various features found in samples produced through the SLE technique and a data analysis program that provides greater insights into how the SLE settings influence the microstructure. Using this program the isolation of optimal SLE settings is faster while also providing greater insights into the process than is currently possible. The microstructure recognition program features three key aspects. The first evaluates major characteristics that typically arise during the SLE process; such as sample deformation, the aspects of a single crystal deposit, and the total deposit height. The second saves the data and all relevant test settings in a format that will allow for future analysis and comparison to other samples. Finally, it features a robust yet rapid execution so it may be used for entire runs of SLE samples, which can number up to 25, within a week. The program is designed for the types of microstructure found in CMSX-4 and Rene-80, specifically single crystal and equiaxed regions. The data fitting program uses optimally piecewise-fitted equations to find relationships between the SLE settings and the microstructure traits. The data is optimally piecewise fitted as the SLE process is a two-stage procedure, establishing then propagating the melt-pool across a sample, which creates distinct microstructure transitions. Using the information gathered, graphs provide a visual aid to better allow the experimenter to understand the process and a DOE is performed using sequential analysis; allowing the previously run samples to influence the future trials, reducing the amount of materials used while still providing great insight into the parameter field. Having access to the microstructure data across the entire sample and an advanced data fitting program that can accurately relate them to the SLE settings allows the program to track and optimize features that were never before possible.

Scanning Laser Epitaxy (SLE) is a new layer-by-layer additive manufacturing process being developed in the Direct Digital Manufacturing Laboratory at Georgia Tech. SLE allows for the fabrication of three-dimensional objects with specified microstructure through the controlled melting and re-solidification of a metal powder placed atop a base substrate. This dissertation discusses the work done to date on assessing the feasibility of using SLE to both repair single crystal (SX) turbine airfoils and manufacture functionally graded turbine components. Current processes such as selective laser melting (SLM) are not able to create structures with defined microstructure and often have issues with warping of underlying layers due to the high temperature gradients present when scanning a high power laser beam. Additionally, other methods of repair and buildup have typically been plagued by crack formation, equiaxed grains, stray grains, and grain multiplication that can occur when dendrite arms are separated from their main dendrites due to remelting. In this work, it is shown that the SLE process is capable of creating fully dense, crack-free equiaxed, directionally-solidified, and SX structures. The SLE process, though, is found to be currently constrained by the cumbersome method of choosing proper parameters and a relative lack of repeatability. Therefore, it is hypothesized that a real-time feedback control scheme based upon a robust offline model will be necessary both to create specified defect-free microstructures and to improve the repeatability of the process enough to allow for multi-layer growth. The proposed control schemes are based upon temperature data feedback provided at high frame rate by a thermal imaging camera. This data is used in both PID and model reference adaptive control (MRAC) schemes and drives the melt pool temperature during processing towards a reference melt pool temperature that has been found to give a desired microstructure in the robust offline model of the process. The real-time control schemes will enable the ground breaking capabilities of the SLE process to create engine-ready net shape turbine components from raw powder material.