In-situ 3D temperature field modeling and characterization using eddy current for metal additive manufacturing...

Metal additive manufacturing (AM) is a critical capability for Industry 4.0, with particular potential in the aerospace and medical industries. Its ability to create dense metal parts with intricate geometries makes it appealing for demanding environments requiring specific thermal and mechanical properties, as well as long-term reliability. Despite its potential, challenges such as low surface quality and buried porosity have impeded the widespread adoption of metal AM. Therefore, advances such as real-time monitoring of AM processes are necessary to realize the full capability of these new manufacturing methods. Here we examine the feasibility of one promising approach: eddy current (EC) measurements for in-situ LPBF AM temperature monitoring, which is different from existing EC method to monitor near surface porosity or crack. The temperature-dependent electrical conductivity of many materials used in AM processes suggests it may be possible to measure the internal temperature using an eddy current probe. These measurements of the temperature history could then inform the quality of build layers, such as internal stress, which would otherwise be inaccessible to characterization. We first developed a thermally-coupled electromagnetic simulation to examine this phenomenon. Our model reveals a complex internal temperature distribution created during dynamic laser heating processes. Notably, the simulation also indicates that the EC response can dynamically reflect the temperature of the AM material during both the heating and cooling processes. We performed experiments to validate our simulations, using a soldering iron tip as a point heating source on a metal plate, together with a commercial EC apparatus. The results showed that this method can achieve real-time temperature monitoring in the range 420-700 K, suggesting potential for addressing a critical need process monitoring need for enhancing metal AM processes.