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Advanced Manufacturing Data Infrastructure and Analytics Program

Program Manager: Simon Frechette
The Advanced Manufacturing Data Infrastructure and Analytics (AMDIA) program will lay the groundwork for advanced data infrastructure and corresponding analytics to improve the productivity, resiliency, security, and sustainability of manufacturing operations and enterprises across the supply chain. As the manufacturing industry produces increasing volumes of diverse data, stakeholders need robust data infrastructure and trusted analytics to prepare, model, understand, and utilize their data effectively and efficiently for improved control and better decision-making. Emerging technologies allow manufacturers to collect, structure, link, and analyze data in new ways. However, technologies are seldom one-size-fits-all solutions. Research into manufacturing data and the role of human expertise in the process is needed to effectively adopt and integrate solutions into existing operations. 

Measurement Science for Additive Manufacturing Program

Program Manager: Shawn Moylan
This program addresses measurements and standards necessary to develop and deploy advances in measurement science that will enable rapid design-to-product transformation; material characterization; in-process process sensing, monitoring, and model-based optimal control; performance qualification of materials, machines, processes and parts; and end-to-end digital implementation of Additive Manufacturing (AM) processes and systems.  Reducing the barriers to widespread implementation and use of AM, such as high level of process variability, low part accuracy and surface quality, and inconsistent material properties, lack of process and part qualification and certification methods, and lack of adequate, well-controlled and traceable measurement data and analysis tools to validate and improve AM process models for better understanding of the processes and their outcomes, as well as resulting methods for decision support (i.e. predictive analytics and design guidelines) will be a main goal of the program. The program will develop: standardized material characterization methods, exemplar data and databases to accelerate the design, processing, and use of AM parts; process metrology, sensing and control methods and algorithms to maximize part quality and production throughput in AM; test methods, protocols, and reference data to reduce the cost and time to qualify AM materials, processes, and parts; and an information systems architecture, including metrics, information models, and validation methods to shorten the design-to-product cycle time in AM.  It is anticipated that this programmatic effort will facilitate: accelerated proliferation of AM parts in high-performance applications benefiting from AM's unique capabilities; improved quality and throughput for AM;  rapid qualification of AM materials and processes leading to better understanding of AM and more confidence in AM products used in industry; and streamlined design-to-product transformations leading towards more accessible AM technologies for small and medium-sized companies, increasing industrial competitiveness.

Created August 22, 2019, Updated September 8, 2022