Controlling Material Deposition in Wire-Based Welding and Additive Manufacturing

On-going resource challenges with global supply chains and workforce populations in the energy sector have prompted increasing attention on deposition techniques for fabrication of large metal components. To this end, research is using digital manufacturing to control the fabrication of metal structures by integrating wire-based manufacturing techniques with robotic automation and multi-mode sensing. Arc based welding processes, specifically gas metal arc welding (GMAW) and gas tungsten arc welding (GTAW), are the primary focus and have been explored for steel, bronze and aluminum alloys using multi-axis robotic manipulators. Process development has explored and determined process conditions whereby bead geometry, layer height, as-printed microstructure and material properties are stable and repeatable. Multi-mode sensing has been integrated across deposition systems to provide real-time monitoring of process and equipment states. Hardware and software for optical, thermal, and acoustic sensing modalities are now operational, and synchronized with arc waveform and robot motion trajectory data during deposition. On-going work is focused on identifying critical process signatures and developing correlations with important process outcomes such as melt pool behavior, material interpass temperature, deposited bead geometry and final part shape. These correlations are being examined using data analytic techniques ranging from conventional regression to machine learning and neural networks. Further, workflows have been developed for robotic path planning of parts that incorporate non-planar and non-gravity aligned features, varying wall thicknesses and complex, freeform geometries. Integration of path planning with process monitoring is a future objective that remains critical to controlling and automating wire-based metal deposition techniques. Such control is necessary to improve the quality and reliability of printed materials, to improve the accuracy of final part geometries, and to address growing needs for the efficient and expedient production of large metal components.