Graduate Student Seminar

Abstract: Qualifying additively manufactured components for critical applications is a significant bottleneck, as it traditionally requires extensive mechanical testing. To accelerate deployment timelines, this presentation introduces Delta Qual, a data-rich transfer framework for LPBF Ti-6Al-4V that leverages in-situ process monitoring (optical tomography, melt pool monitoring, spatter tracking) to establish statistically informed equivalency criteria without requiring exhaustive empirical retesting. The framework was validated through a phased hardware variability study: intra-model (EOS M290 serial numbers), intra-OEM scaling (M400 platforms), and cross-OEM architectures (Concept Laser, AMCM). Mechanical validation revealed a critical performance divergence. Static tensile properties demonstrated high portability across all platforms (UTS clustered at 1050–1115 MPa), indicating static requalification can be dramatically streamlined. Conversely, fatigue performance proved sensitive to platform variability, isolating dynamic loading as the primary transfer risk. By replacing redundant testing with evidence-based digital validation, Delta Qual provides an accelerated pathway that significantly reduces qualification cost, time, and experimental burden. Dr. Yash Parikh, a Process Engineering Consultant at EOS North America, brings over a decade of expertise in additive manufacturing (AM), specializing in qualification and validation protocols for EOS’s systems. He has secured over $5 million in research funding as a principal investigator (PI) and co-PI from agencies including AFRL, ONR, America Makes, and LIFT. Before joining EOS, he was a Postdoctoral Research Associate at Carnegie Mellon University’s NextManufacturing Center, where he advanced AI/ML applications for expeditionary manufacturing for an ARL-funded project. His doctoral research at Texas A&M University on property-graded single-alloy bulk structures produced by laser powder bed fusion resulted in multi