This technology addresses the problem of sparse and inconsistent data from CNC machine controllers that operate at limited sampling rates. It enables manufacturers to create a higher-resolution, standardized representation of machining activity using existing controller information and available operational context. The approach improves visibility into machine behavior, supports more reliable comparison between production runs, and enables G-code–level performance analysis. As a result, manufacturers can better detect anomalies, improve operational decision-making, and reduce unplanned downtime without modifying machine hardware.
Description
CNC controllers often report machine information at low and non-uniform sampling rates, which can obscure short events, prevent accurate reconstruction of tool motion, and limit cross-run comparison. This technology provides an offline data enhancement workflow that increases the effective resolution and consistency of CNC machine data using information already available within the manufacturing environment.
The method integrates machine controller data with posted part programs and, when available, additional synchronized operational signals. It identifies operational states, separates production and non-production segments, and aligns sparse machine samples to the corresponding programmed toolpath context. Missing or irregular samples are reconstructed through controlled data expansion and feature-based interpolation, producing a continuous and uniform dataset.
The resulting standardized data structure enables G-code-level analysis of productivity metrics, improved identification of abnormal machine behavior, and consistent comparison across machines and runs. The technology supports development of advanced monitoring and modeling workflows, including digital representations of machining processes, while avoiding changes to existing CNC hardware or controllers.
Benefits
- Improves visibility into short-duration and transient machining events
- Enables consistent, high-resolution machine data across production runs
- Supports earlier detection of process anomalies
- Enhances reliability of machine productivity and performance metrics
Applications and Industries
- Discrete manufacturing and machining operations
- CNC equipment monitoring and analytics platforms
- Aerospace, automotive, and precision manufacturing
- Industrial digital modeling and process optimization
Contact
To learn more about this technology, email [email protected] or call 865-574-1051.
Contact
To learn more about this technology, email [email protected] or call 865-574-1051.