Thesis Research

Intensity-Based Registration With Voxel-Based Computer-Aided Manufacturing for Adaptive Machining

Unique topics researched/implemented:

  • Digital Twin

  • Maximization of Mutual Information (Shannon Entropy)

  • Genetic Algorithm Optimization

  • Particle Swarm Optimization

  • Simulated Annealing

  • Iterative Closest Point

  • Voxels Representations

Overview of Research:

My Master's thesis research began by examining a method to generate gcode needed to machine a part when CAD models either do not exist or are not practical to construct.

The technique was presented in the context of machining irregularly shaped materials. Machining of investment castings, hybrid manufacturing, and CT integrated systems are several areas of application. In each case, a Digital Twin type representation of the pre-machined part is aligned with a desired final model for toolpath calculations.

This research not only contributed to the body of knowledge by presenting a novel approach to a manufacturing problem for further exploration, but also serves as an example of how I can quickly learn and implement new skills to complete a project.

My work was published in the ASME Journal of Manufacturing Science and Technology Vol.141(11)

 
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