NASA’s Office of Safety and Mission Assurance Quality Initiatives Program sponsored a half day workshop on Quality Assurance in Additive Manufacturing (AM) at Aerospace Corporation Headquarters in El Segundo, California. The workshop, held in association with Aerospace’s Manufacturing Problem Prevention Program — or MP3 — and Additive Manufacturing Guidance Development Workshop, focused on the theme of “Quality Strategies for AM.” Speakers at the NASA AM portion included NASA centers, national labs and AM manufacturing industry representatives, as well as industrial risk analysis companies.
Part of the workshop highlighted how the continual maturation and evolution of AM technologies challenges the historical concept of part and sample qualification.
“Additive Manufacturing is uniquely suited to provide custom solutions that are not high-volume, repeatable solutions,” said Doug Sheldon, Assurance Technology Program Office manager at the Jet Propulsion Laboratory. “Qualifying unique, one-of-a-kind items with individual idiosyncrasies represents an important part of this challenge.”
Keynote speaker Ian Wing of Deloitte Consulting highlighted how typically qualification is built around a combination of standards, calibration, raw materials control, and historical or heritage data. Because AM allows for both rapid prototyping as well as customization near the point of use, the impact on the usual view of the supply chain is significant. Inventories can be significantly reduced because of this. At the most extreme cases of application to mass customization, this could result in a true disintermediation of the overall supply chain. Ultimately, this can result in a higher performance process, higher levels of quality and lower levels of risk, and quicker turnaround times. These changes are driven by the rapid acceleration of data-driven manufacturing, sometimes called “Industry 4.0.”
Industry 4.0 means manufacturing efficiencies and improvements in quality are tied to information management and information assurance technologies, resulting in more use of sophisticated process and build modeling tools early in the design phase, as well as the use of in-situ sensing and measurement data. Challenges for this type of data-driven manufacturing include dramatic increases in the volumes of relevant data as well as abilities to manage and to protect it as a cyber resource. As Sheldon explains, protecting digital information from risks, like hackers is paramount.
Ibo Matthews of Lawrence Livermore National Laboratory provided an example of this data-driven manufacturing with a demonstration of a Model-Based Intelligent Feed Forward approach. For a laser-based power bed fusion system, defect mitigation steps such as power and speed mapping for part-specific geometry controls were extended and enhanced with the model-based approach.
The workshop also focused on the current state-of-the-art of AM. Ken Davies of CalRAM provided a detailed case study and lessons learned of the AM Planetary Instrument for X-ray Lithochemistry — or PIXL — instrument structure that will be used on the upcoming Mars 2020 rover mission.
Eric Fodran of Northrup Grumman reviewed the details and issues associated with producing the large (890 unique test samples) Electron Beam Meltig-based Ti-6Al-4V design allowables database. He covered best practices for build design as well as improvements in the X-ray Nondestructive Inspection procedures. Finally, a panel discussion concluded the workshop to address how to increase the Technical Readiness Level of AM products given the current, as well as planned, capabilities.