Data-driven manufacturing is reshaping the future of Directed Energy Deposition (DED) by integrating intelligence directly into the fabrication process. FormAlloy’s DEDSmart® technology combines real-time in-situ monitoring with comprehensive post-build data analysis to deliver greater precision, repeatability, and reliability in additive manufacturing. This integrated approach leverages advanced sensors, high-speed data acquisition, and closed-loop control to provide continuous insight into melt pool dynamics, material flow, and thermal gradients—enabling proactive adjustments during deposition.
In-situ data collection allows immediate correction of deviations such as geometric inconsistencies, porosity formation, or variations in microstructure. Meanwhile, post-build data analytics—including three-dimensional spatial mapping of process conditions—establish a complete digital record for each component. This digital traceability accelerates qualification and supports a data-driven certification pathway, essential for high-consequence applications in aerospace, defense, and energy industries where part integrity is critical.
By correlating in-process parameters with resulting material properties, DEDSmart® empowers engineers to optimize builds, shorten development cycles, and reduce costly rework. The resulting process intelligence enables adaptive control strategies that ensure consistent deposition across a wide range of alloys and complex geometries.
This presentation will highlight case studies demonstrating how DEDSmart® transforms traditional DED into a self-monitoring, self-correcting process. Examples include defect mitigation through real-time control, accelerated parameter optimization, and the creation of a “digital thread” linking process data to material performance.
By making the case for data-centric manufacturing, FormAlloy’s DEDSmart® technology establishes a foundation for intelligent, certifiable additive manufacturing—paving the way for faster qualification, improved process confidence, and the next generation of smart, high-performance metal components.
Learning Objectives:
Upon completion, participants will be able to understand how in-situ process control can be used to accelerate process parameter development in DED applications.
Upon completion, participants will be able to describe the types of defects that in-situ process control and data logging can correct and detect.
