Material Composition Sensing for Additive Manufacturing Based on Cooling Rate Monitoring

Abstract

Additive manufacturing (AM) has become a widely applied process to print polymer and metallic parts in small scale. In recent years, AM processes and instruments are developed to print structure with two or multiple materials to form alloy during printing. The material composition in the printing process became a critical issue in determining the quality of the printed part. This paper presents a new approach to detect the metal material composition in the printed structure through thermal imaging. This approach tests the temperature variation and cooling rate of the melt metal during it is cooling down to solid. Through a theoretical model, it is proved that the cooling rate is a function of the material thermal properties, which can be made use of for retrieving the material composition. For copper-Inconel 625 alloy, an alloy widely studied in metal additive manufacturing technology, the theoretical model shows that the cooling rate monotonically increases with the increase of copper’s weight percentage at constant temperature. Such a relationship is also experimentally tested by using a high-speed camera observing the process of Laser Powder Bed Fusion (L-PBF). The experimental results validate the relationship given by the theoretical model. It shows that the developed technique is able to serve as a new methodology to measure the alloy composition in real-time, for improving the consistency of mechanical/thermal properties of the printed parts.