facturing variability. Dr. Margiotta explained the guiding principles for DARPA’s Open Manufacturing program:

  • Identify critical parameters, variation, and limits early in the process.
  • Reduce testing and development iterations.
  • Predict location-specific probabilistic performance.
  • Build confidence in new technologies or qualification processes.
  • Accelerate process maturity and systematic process reassessment.

Dr. Margiotta then described a project DARPA is developing with Honeywell Aerospace and several other team members. The project aims to develop rapid qualification of powder bed fusion additive manufacturing processes—in particular, direct metal laser sintering (DMLS). The general approach consists of the following elements: parameterize the manufacturing process; implement new sensors into the manufacturing process; incorporate an ICME construct that links process to materials to properties; and apply rigorous model verification and validation to understand the confidence limits. In this way, process parameters are linked to quantified, location-specific properties of the as-manufactured part. Dr. Margiotta showed a schematic of the critical elements for rapid qualification (Figure 4). The constituents to enable rapid qualification are shown in blue at the top of the figure. The supporting elements are shown below that; many of them—such as sensing, linking sensing capability to quality assurance, and microstructure property models—still need to be developed. Dr. Margiotta pointed out that the business cases and implementation plan are particularly important, as they will affect the usage and acceptance by the broader community. He stated that the architecture consists of increasing layers of complexity, including difficulties with the interfaces between different elements of the system.

Dr. Margiotta then explained the informatics associated with the additive manufacturing process. First, experiments are conducted to define the processing window, which is then refined through additional experiments to determine the optimal site within that window. This leads to a semioptimized process and overall improved material properties. The energy input density can also be measured and correlated with the quality of the consolidated material. In addition, the build chamber is instrumented to provide real-time monitoring of process parameters. The sensors have been able to capture a large quantity of high-fidelity data; at this point, about 1 TB of sensor data are collected for each DMLS build.

Dr. Margiotta then moved to the ICME construct, which uses process–microstructure–performance models to simulate the manufacturing process. Dr. Margiotta explained that the current simulation takes several days to a week to complete, which is much too long. These tools need to be further developed and simplified. The ICME construct consists of the following elements:

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