Additive Manufacturing: Equipment, Instrumentation and In-Situ Process Monitoring: Poster Session
Sponsored by: TMS Additive Manufacturing Committee
Program Organizers: Ulf Ackelid, Freemelt AB; Joy Gockel, Colorado School Of Mines; Sneha Prabha Narra, Carnegie Mellon University; Ola Harrysson, North Carolina State University

Monday 5:00 PM
October 10, 2022
Room: Ballroom BC
Location: David L. Lawrence Convention Center


A-18: Development of an IEP Apparatus for 3D Printing of Thermoelectric Material: Weixiao Gao1; Fei Ren1; 1Temple University
    Additive manufacturing, commonly known as 3D printing, has become increasingly attractive in recent years due to some unique advantages, such as complex shape design, mold-free fabrication, high materials usage rate, etc. In the field of thermoelectric research and development, AM technologies have gradually been involved in the manufacturing and application of thermoelectric materials and devices. Due to the flexible manufacturing capability and unique personal customization ability, AM technologies can significantly promote the application of thermoelectric materials and reduce costs. Based on our previous work of metal 3D printing, we designed and fabricated an ink extrusion printing (IEP) apparatus for additive manufacturing of thermoelectric materials. In particular, we designed and tested printing inks for bismuth telluride thermoelectric material. In this presentation, we will discuss the construction of the IEP 3D printer and demonstrate its capability to fabricate thermoelectric materials.

A-19: In-process Microstructure Sensing of Gr91 Powder Bed Fusion Parts Using Ultrasonics: Nathan Kizer1; Christopher Kube1; Edward Reutzel1; Corey Dickman1; 1Penn State University
    Gr91 stainless steel (9Cr-1Mo) is common in power plant components because of its high temperature creep strength. In traditional Gr91 components, the strength results from heat treatment steps toward forming a martensitic microstructure. Recently, efforts in the materials research community have attempted to recreate the desired microstructure using only additive manufacturing (AM) processes. Our work continues this thread. However, our focus is on developing an in-process powder bed fusion sensing modality capable of discerning variations in Gr91 microstructures across an array of coupons manufactured with different process parameters. The sensing modality is based on in situ ultrasonic sensors integrated into a build substrate with one sensor under each part coupon. This presentation will highlight multiple measured ultrasonic parameters and assess their sensitivity to the microstructures obtained. Enabling this capability is expected to bring rapid in-process characterization of microstructure relevant to efforts attempting to custom tailor microstructures during AM processes.

A-20: Real-time Process Monitoring for Multivariate Statistical Process Control in Powder Bed Fusion Metal Additive Manufacturing: Venkatavaradan Sunderarajan1; Suman Das1; 1Georgia Institute of Technology
    The application of Multivariate Statistical Process Control (MSPC) to optimize Powder bed Fusion (PBF) metal Additive Manufacturing (AM) process parameters, as well as to continuously track and adjust them is presently at a low level of maturity. The ability to implement MSPC will ubiquitously bolster industry sectors where PBF metal AM adoption is currently hindered by the absence of a reliable framework for quality control. It is critical to establish reliable relationships between the AM process parameters and the process/part characteristics. Herein, the instrumentation used to facilitate real-time process monitoring for this purpose shall be demonstrated. Various instruments, their specific characteristics, the corresponding process information gathered as well as the data generation relevant to capturing the real-time physics of the process will be comprehensively detailed. This will enable us to validate currently known relationships between process variables and part quality metrics and to elucidate hitherto obscure and potentially complex ones.

A-21: Quantification of Melt Pool Variability for L-PBF Additive Manufacturing by High-Speed Imaging: David Guirguis1; Conrad Tucker1; Jack Beuth1; 1Carnegie Mellon University
    Laser powder bed fusion (L-PBF) is one of the well-established metal additive manufacturing technologies in the market. Insights into the variability of melt pool dimensions are crucial to determine process parameters for process optimization and enhancement of mechanical properties. Specifically, melt pool dimensional variability can lead to lack-of-fusion type flaws. In the present work, we analyze the variation in melt pool dimensions by utilization of ultra-high-speed imaging at a rate of up to 200,000 frames per second. Quantification of melt pool variation for the titanium alloy, Ti-6Al-4V, is performed with a variety of process parameters. Results from high-speed imaging are compared to direct measurements of bead widths from single bead experiments. Melt pool variability is presented across parameter space in a process map format. Results from high-speed imaging of block and component builds are also presented.