The U.S. economy depends on manufacturing as a significant contributor for jobs, the nation’s economic output, and the production of goods for the world. Likewise, U.S. manufacturing depends on its 500,000+ machine tools that make precision parts. However, a major problem with these machines is that their performance, which degrades over time due to operations, is typically not monitored, resulting in unplanned downtime and the loss of revenue as machines fail or machined parts exceed their specifications without warning. Hence, manufacturing needs smart machine tools that are self-aware via on-machine measurements and diagnostics, to track the machine’s performance health. Furthermore, solutions must be non-invasive, data-rich, inexpensive, and accurate to be used by every machine tool to enable optimized production of assets within manufacturing facilities. Augmented intelligence, which is the augmentation of traditional scientific intelligence with artificial intelligence (AI) to provide humans with actionable intelligence, is envisioned as a disruptive catalyst for this future of smart manufacturing. 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. Smart machine tools assess and predict their health and the performance of their processes in real time to optimize production quality and yield.

Proposals are welcome to develop augmented intelligent solutions for smart machine tools. For example, new methods may be developed for the monitoring of rotary or linear axes, ball screw preload and backlash, spindle performance, real-time cutting forces, or thermal drift, among many other possible topics. Our facilities support experimental work via laboratory testbeds and numerous machining centers in a shop environment. 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.

key words

Smart manufacturing; Intelligent manufacturing; Advanced manufacturing; Subtractive manufacturing; Hybrid manufacturing; Data-driven manufacturing; Manufacturing; Production; Industry 4.0; Advanced intelligence; Artificial intelligence; AI; Data-driven science; Machine learning; ML; Augmented intelligence; Machines; Machine tools; Production machines; Hybrid machine tools; Measurement science; Metrology; Sensors; Technology transfer

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral applicants