Metallic Additive-Manufacturing using laser sintering to fabricate parts layer-by-layer directly from a 3D computer model has emerged and has grown rapidly in the past decade. Such technology can significantly reduce time-to-market, improve product quality, reduce material-waste, and reduce cost. This project will help overcome important roadblocks that currently exist before this technology can be widely adopted. This research will use eddy current-based novel sensing mechanism during manufacturing process that will enable precision in manufacturing along with reduced cost. This technique will allow a robust layer-by-layer quality assessment while the part is being fabricated and the production rates will be expedited eliminating post-build inspection or destructive testing. While the method is in the context of metal additive manufacturing, the underlying system architecture and ideas can be extended to spawn a spectrum of different applications; for example, new medical applications such as magnetic induction tomography for accurate diagnosis of intracerebral hemorrhage. Several industries may benefit, including the automotive, the aerospace, the medical and healthcare, and industrial manufacturing sectors. The project also includes interesting K-12 outreach efforts in addition to curriculum development.
The objective of the research is to develop a novel methodology to model a distributed-parameter system, reconstruct its physical fields and infer its system properties from limited measurements for analyzing and controlling its dynamic behaviors. A novel multi-target sensing methodology based on a set of multi-frequency eddy-current sensing will be developed for reconstructing the physical fields which measure geometrical parameters as well as detect surface and subsurface defects during the machining process. The work will also formulate dynamic model of the thin-walled plate during machining, and develop efficient methods for reconstructing its displacement, strain and stress fields from limited displacement measurements in real time for monitoring and controlling the dynamics of the distributed-parameter system. Unlike traditional single-frequency eddy-current sensors the multi-target sensing system can adaptively synthesizes a relatively high-resolution eddy-current pattern between adjacent coils with a combination of appropriate frequencies to simultaneously determine the displacement, thickness and electrical conductivity. The distributed current source (DCS) modeling method for sensor design and analysis is highly efficient and reduces computational complexity. It is expected that the ability to reconstruct the multi-physical fields (electric, magnetic, displacement, force, strain and stress) from the multi-target sensors and field reconstruction algorithms during part fabrication not only will offer intuitive insights into the effects of several critical factors (such as material mechanical properties, boundary geometrical/clamping constraints and damping coefficients) on thermal/machining induced residue stresses that are generally the main cause of thin-walled product distortions, and but also will provide an essential basis to vibration suppression.
