Ni/TiC metal matrix composites have been processed using the laser engineered net shaping (LENS) process. As nickel does not form an equilibrium carbide phase, addition of a strong carbide former in the form of titanium reinforces the nickel matrix resulting in a promising hybrid material for both surface engineering as well as high temperature structural applications. Changing the relative amounts of titanium and carbon in the nickel matrix, relatively low volume fraction of refined homogeneously distributed carbide precipitates, formation of in-situ carbide precipitates and the microstructural changes are investigated. The composites have been characterized in detail using x-ray diffraction, scanning electron microscopy (including energy dispersive spectroscopy (XEDS) mapping and electron backscatter diffraction (EBSD)), Auger electron spectroscopy, and transmission (including high resolution) electron microscopy. Both primary and eutectic titanium carbides, observed in this composite, exhibited the fcc-TiC structure (NaCl-type). Details of the orientation relationship between Ni and TiC have been studied using SEM-EBSD and high resolution TEM. The results of micro-hardness and tribology tests indicate that these composites have a relatively high hardness and a steady-state friction coefficient of ~0.5, both of which are improvements in comparison to LENS deposited pure Ni.

A compositionally graded Ti-xCr (10≤x≤30 wt%) alloy has been fabricated using Laser Engineered Net Shaping (LENSTM) to study the microstructural phase evolution along a compositional gradient in both as-deposited and heat treated conditions (1000°C followed by furnace cooling or air cooling). The alloys were characterized by SEM BSE imaging, XRD, EBSD, TEM and micro-hardness measurements to determine processing-structure-property relations. For the as-deposited alloy, α-Ti, β-Ti, and TiCr2 (C15 Laves) phases exist in varying phase fractions, which were influential in determining hardness values. With the furnace cooled alloy, there was more homogeneous nucleation of α phase throughout the sample with a larger phase fraction of TiCr2 resulting in increased hardness values. When compared to the air cooled alloy, there was absence of wide scale nucleation of α phase and formation of ω phase within the β phase due to the quicker cooling from elevated temperature. At lower concentrations of Cr, the kinetics resulted in a diffusionless phase transformation of ω phase with increased hardness and a lower phase fraction of TiCr2. In contrast at higher Cr concentrations, α phase separation reaction occurs where the β phase is spinodally decomposed to Cr solute-lean β1 and solute-rich β2 resulting in reduced hardness.

Indiana University-Purdue University Indianapolis (IUPUI) / This thesis proposes an automated grid-based alignment system utilizing lasers and an array of light-detecting photodiodes. The intent is to create an inexpensive and scalable alignment system for pick-and-place robotic systems. The system utilizes the transformation matrix, geometry, and trigonometry to determine the movements to align the robot with a grid-based array of photodiodes. The alignment system consists of a sending unit utilizing lasers, a receiving module consisting of photodiodes, a data acquisition unit, a computer-based control system, and the robot being aligned. The control system computes the robot movements needed to position the lasers based on the laser positions detected by the photodiodes. A transformation matrix converts movements from the coordinate system of the grid formed by the photodiodes to the coordinate system of the robot. The photodiode grid can detect a single laser spot and move it to any part of the grid, or it can detect up to four laser spots and use their relative positions to determine rotational misalignment of the robot. Testing the alignment consists of detecting the position of a single laser at individual points in a distinct pattern on the grid array of photodiodes, and running the entire alignment process multiple times starting with different misalignment cases. The first test provides a measure of the position detection accuracy of the system, while the second test demonstrates the alignment accuracy and repeatability of the system. The system detects the position of a single laser or multiple lasers by using a method similar to a center-of-gravity calculation. The intensity of each photodiode is multiplied by the X-position of that photodiode. The summed result from each photodiode intensity and position product is divided by the summed value of all of the photodiode intensities to get the X-position of the laser. The same thing is done with the Y-values to get the Y-position of the laser. Results show that with this method the system can read a single laser position value with a resolution of 0.1mm, and with a maximum X-error of 2.9mm and Y-error of 2.0mm. It takes approximately 1.5 seconds to process the reading. The alignment procedure calculates the initial misalignment between the robot and the grid of photodiodes by moving the robot to two distinct points along the robot’s X-axis so that only one laser is over the grid. Using these two detected points, a movement trajectory is generated to move that laser to the X = 0, Y = 0 position on the grid. In the process, this moves the other three lasers over the grid, allowing the system to detect the positions of four lasers and uses the positions to determine the rotational and translational offset needed to align the lasers to the grid of photodiodes. This step is run in a feedback loop to update the adjustment until it is within a permissible error value. The desired result for the complete alignment is a robot manipulator positioning within ±0.5mm along the X and Y-axes. The system shows a maximum error of 0.2mm in the X-direction and 0.5mm in the Y-direction with a run-time of approximately 4 to 5 minutes per alignment. If the permissible error value of the final alignment is tripled the alignment time goes down to 1 to 1.5 minutes and the maximum error goes up to 1.4mm in both the X and Y-directions. The run time of the alignment decreases because the system runs fewer alignment iterations.