NIST - National Institute of Standards and Technology
01/29/2026 | Press release | Distributed by Public on 01/30/2026 03:19
DATA REQUIREMENTS FOR A DIGITAL TWIN OF A CNC MACHINE TOOL
Published
January 29, 2026
Author(s)
Deogratias Kibira, Guodong Shao
Abstract
Digital twins enable the intelligent operation of computer numerical control (CNC) machine tools from which a wide range of data can be collected using sensors and other Internet of Things (IoT) devices. Creating a valid digital twin for a specific purpose requires identifying and specifying the right types and quality of data. However, there are challenges, such as unlabeled data and a lack of clarity on the sufficiency of data required to build a digital twin for a specific purpose. This paper discusses the data types, sources, and acquisition methods for creating digital twins for machine tools with different capabilities. Depending on the purpose, any digital twin can be categorized as descriptive, diagnostic, predictive, prescriptive, and autonomous. Data requirements for each of these categories are discussed. This paper can be used as a guide for developing and validating different types of digital twins for CNC machine tools.
Proceedings Title
PROCEEDINGS OF THE 2025 WINTER SIMULATION CONFERENCE
Conference Dates
December 7-10, 2025
Conference Location
Seattle, WA, US
Conference Title
2025 WINTER SIMULATION CONFERENCE
Pub Type
Conferences
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Keywords
CNC Machine tool, Digital Twin, Data, Standards
Systems integration, Manufacturing systems design and analysis and Interoperability in manufacturing
Citation
Kibira, D. and Shao, G. (2026), DATA REQUIREMENTS FOR A DIGITAL TWIN OF A CNC MACHINE TOOL, PROCEEDINGS OF THE 2025 WINTER SIMULATION CONFERENCE, Seattle, WA, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=959858 (Accessed January 30, 2026)
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NIST - National Institute of Standards and Technology published this content on January 29, 2026, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on January 30, 2026 at 09:19 UTC. If you believe the information included in the content is inaccurate or outdated and requires editing or removal, please contact us at [email protected]