SUBJECT: Ph.D. Proposal Presentation
BY: Rohan Bansal
TIME: Thursday, September 27, 2012, 9:00 a.m.
PLACE: MARC Building, 201
TITLE: Analysis and Adaptive Feedback Control of the Scanning Laser Epitaxy Process Applied to Nickel-Based Superalloys
COMMITTEE: Dr. Suman Das, Chair (ME)
Dr. Yogendra Joshi (ME)
Dr. Nader Sadegh (ME)
Dr. Jianjun Shi (ISyE)
Dr. Sudarsanam Suresh Babu (The Ohio State University, MSE)


Scanning Laser Epitaxy (SLE) is a new layer-by-layer additive manufacturing process being developed in the Direct Digital Manufacturing Laboratory at Georgia Tech that that allows for the fabrication of three-dimensional objects with specified microstructure through the controlled melting and re-solidification of a metal powders placed atop a base substrate. This proposal discusses the work done to date on assessing the feasibility of using SLE to repair single crystal (SX) turbine airfoils as well as the 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. Other methods of repair and buildup have typically been plagued by crack formation, equiaxed grains, stray grains, as well as grain multiplication that occurred when dendrite arms were separated from their main dendrites due to remelting. The SLE process has shown that it is capable of creating equiaxed, directionally solidified, and SX structures but the process is currently somewhat constrained by the cumbersome method of choosing proper parameters and a relative lack of repeatability. It is hypothesized that real-time feedback control schemes based upon an offline model will be necessary both to create specified defect free microstructures and 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 framerate by a thermal imaging camera as well as a melt-pool viewing video microscope. This data will be used in two different control schemes, a model reference control scheme and a distributed parameter control scheme and will attempt to drive the melt pool temperature during processing towards a desired melt pool temperature that has been found to give a desired microstructure in a robust offline model of the process. If successfully implemented, the real-time control scheme will deliver ground breaking capability to the SLE process in terms of alllowing for the creation of engine ready net shape turbine components from raw powder material.