ADVANCED MATERIALS & PROCESSES | APRIL 2024 1 7 capability to ensure quality at scale. Because of the maturity of the AM industry, an LSI approach is to identify AM parts candidates and develop/ validate AM technical data packages in-house, and then deliver a TDP to qualified vendors for production and post processing. Another challenge identified by LSIs in working with SMEs was the time, money, and effort involved. This is because the AM market is small, so is it worth setting up a qualified supplier? Further, there is a nontraditional customer-supplier relationship, e.g., an LSI can’t just send a drawing, specification and RFQ and expect to get a quality product. Panel 3: Data Consortium and Nonprofit Perspectives. The panel discussed the importance of developing a common AM vocabulary and exchange formats based on a common data model, and that the format should be both machine and human readable. The idea is not to dictate the use of a format, but rather allow the mapping of company internal data to the CDM for exchange purposes. It was also the consensus that there is a need for greater collaboration amongst SDOs. Several positive examples of collaboration were cited. However, it was agreed that progress is slower than desired. Panel 4: Software and Data Analytic Tool Provider Perspectives. The moderator set the stage for the panel by discussing the needs of small and medium sized manufacturers. When asked in a survey about the most urgent needs, 46% of these companies named automation solutions, 13% said additive manufacturing, and 10% listed software. The panel discussed a variety of software options. For example, Applied Optimization has a software called AMP2 that can model the LPBF process on a track-by-track basis and account for feature-specific parameters, significantly reducing surface and volumetric defects. WORKING GROUP OUTCOMES The working groups examined three phases of the AM life cycle during the first two days of the workshop. The phases considered were AM process development, AM part production, and delta qualification and process requalification. The working groups aimed to solicit valuable insight from each attendee and discussions drove the extraction of key workshop findings. Developmental Phase. Challenges identified included issues surrounding data curation, data management, nondestructive evaluation (NDE), and trust. The high cost of data curation and the lack of clarity around the value of the data being collected were considered pain points. In terms of data management, issues included: cost associated with data curation, management, and cyber security; ambiguity over IP ownership; difficulty accessing data across systems and organizations; and lack of automated data acquisition. NDE was of concern, especially regarding a lack of certainty regarding the effect of defects and the absence of low-cost NDE techniques comparable to CT. A perceived lack of trust amongst LSIs and SMEs was identified as a pain point that results in increased cost and time for product realization. Production Phase. Challenges associated with the following were identified: technical data package (TDP), AM production line qualification, workforce, and end-item data package. The lack of an AM TDP standard was a source of pain for SMEs, increasing cost and time. This was especially true for SMEs working with multiple LSIs. The lack of qualification standards was identified as a challenge. Quality standards addressing machine maintenance, process monitoring, and laser power monitoring, as well as the characterization, understanding, and qualification of recycled powder are needed. Other concerns involved workforce competence and the need to enhance automation to reduce human error. Concerns were also raised regarding the cost and time associated with preparing customer required end-item data packages. Standards for end-item data packages were proposed as a solution. Delta Qualification/Requalifica- tion. Two noteworthy challenge areas were identified: cost and data management. It was found that the cost of delta qualification is excessively high as it often involves duplicating the original qualification process. There were concerns regarding data quality and pedigree, as well as access to the TABLE 1 — PERSPECTIVE: SMALL AND MEDIUM SIZED ENTERPRISES Challenge Approach • Lack of understanding of how effective data management can enhance profitability. • Variability in the requirements and structure of technical data packages (TDP). • Compliance with supplier or customer fit-for-purpose requirements. • Accelerate maturation, implementation, and development of standards for a Common Data Model (CDM) and Common Data Exchange Format (CDEF). • Standardize TDP with minimum data requirements. • Develop tools and standards to automate TDP generation. • Publish specific examples of how AM data curation, analysis, and use enables decision making and provides value. • Develop standards for AM production line requalification. • Develop standards for delta qualification. • Lead and support collaboration (LSIs and government) to define the minimum viable data set required for qualification.
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