Machining

News and Updates

Tiny red cylinder probes are presented in front of a much larger ice cube.

Spotlight: Shape-Shifting Probes Will Help Improve MRI Imaging

April 12, 2024

Not all gems are the precious stone kind. In the field of magnetic resonance imaging (MRI), a type of microscopic magnetic probes called geometrically encoded

NIST’s Ultra-small, Shape-shifting GEMS Offer an Easier and Cheaper way to improve MRI Imaging

December 20, 2023

Microscopic magnetic probes that change shape in response to their environment may greatly enhance magnetic resonance imaging (MRI). However, producing the

NIST Researcher Presents on Use of SimPROCESD Software to Model Manufacturing Production and Maintenance

December 1, 2023

At the 2023 INFORMS Annual Meeting, NIST researcher Mehdi Dadfarnia presented research findings based on use of NIST-developed SimPROCESD software, which can

Projects and Programs

Augmented Intelligence for Manufacturing Systems (AIMS)

Ongoing

Objective To overcome existing measurement challenges via augmented intelligence, the fusion of integrated metrology, physics-based models, and artificial intelligence, to enable monitoring, diagnostics, and prognostics of manufacturing systems and their processes. Technical Idea One research

Publications

Towards a Digital Twin of a Robot Workcell: Standards and Methods

October 28, 2024

Author(s)

Deogratias Kibira, Guodong Shao, Rishabh Venketesh

Digital twins are poised to improve the way products are designed, manufactured, and managed throughout their life cycle. However, implementing digital twins

Physics-Informed Multi-Task Learning for Material Removal Rate Prediction in Semiconductor Chemical Mechanical Planarization

August 13, 2024

Author(s)

M. Wahidur Rahman, Gregory W. Vogl, Xiaodong Jia, Yongzhi Qu

The chemical mechanical planarization (CMP) process is a complex and critical operation in the semiconductor manufacturing industry, involving a wide variety of

Building a Digital Twin of a CNC Machine Tool

April 12, 2024

Author(s)

Deogratias Kibira, Guodong Shao, Rishabh Venketesh, Matthew Triebe

Developing digital twins for manufacturing applications is challenging due to insufficient modeling frameworks and standardized procedures. As a result, the

Cutting force estimation from machine learning and physics-inspired data-driven models utilizing accelerometer measurements

November 13, 2023

Author(s)

Gregory W. Vogl, Yongzhi Qu, Reese Eischens, Gregory Corson, Tony Schmitz, Andrew Honeycutt, Jaydeep Karandikar, Scott Smith

Monitoring cutting forces for process control may be challenging because force measurements typically require invasive instrumentation. To remedy this situation