Manufacturing systems are needed that rely on augmented intelligence, the fusion of integrated metrology, physics-based models, and artificial intelligence (AI). Augmented intelligence is envisioned as a disruptive catalyst for process optimization, component verification, and process control. For example, manufacturers desire smart production machines that assess and predict their own health and the performance of manufacturing processes in real time to optimize production quality, resiliency, and sustainability. Augmented intelligent solutions use on-machine sensors for measurements before and during manufacturing processes, analyze the data with a fusion of metrological approaches and machine learning, and monitor and predict the performance of machines and their processes. For subtractive machine tools, measurement challenges for accurate parts production include augmented intelligence for positioning axes (rotary and linear), alignment of axes, ball screw preload, spindle performance, real-time cutting forces, and thermal drift. Similarly, semiconductor manufacturing is a complex procedure with challenging variations in machines and processes. For semiconductor manufacturing, measurement challenges for future-generation chips production include augmented intelligence for wafer inspection, control-process-quality relationships, advanced packaging, and non-planar nanoscale transistors, such as gate-all-around (GAA) field-effect transistors (FETs).

Proposals are welcome to develop augmented intelligent solutions for subtractive, hybrid, and/or semiconductor manufacturing systems. For example, new methods may be developed to estimate cutting forces during milling of materials fashioned from additive manufacturing, track thermal drift of machine tools in real time during parts production, or diagnose deviations during semiconductor manufacturing. Our facilities support experimental work via laboratory testbeds, numerous machining centers, and a nanoscale science center. Collaborations with manufacturers are also highly encouraged. Furthermore, NIST provides computational resources and has an interest group for AI that regularly meets, giving the successful applicant an opportunity to interact with a variety of NIST engineers and scientists.

Keywords:

Smart manufacturing; Intelligent manufacturing; Advanced manufacturing; Subtractive manufacturing; Hybrid manufacturing, Additive manufacturing, Semiconductor manufacturing; Advanced packaging; Sustainable manufacturing; Data-driven manufacturing; Manufacturing; Production; Industry 4.0; Advanced intelligence; Artificial intelligence; Data-driven science; Machine learning; Machines; Machine tools; Production machines; Semiconductors; Measurement science; Metrology; Sensors; Technology transfer

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral applicants