Invention Reference Number
Misalignment of CNC machine tool axes leads to dimensional inaccuracies, extended downtime, and costly, labor-intensive correction efforts. This technology addresses the challenge by using advanced computational modeling to guide machine alignment in a more predictable and efficient manner. By translating measured misalignments into actionable adjustment guidance, the approach reduces reliance on trial-and-error methods and operator intuition. The result is faster alignment, improved machine accuracy, and reduced operational disruption for manufacturing environments.
Description
Conventional CNC machine tool alignment often depends on the experience of skilled operators using iterative adjustment methods that can take weeks to complete. This technology introduces a modeling-assisted approach that leverages digital representations of machine structures to inform alignment decisions. An idealized digital model of key machine components is compared against measured misalignment data to generate a computational representation of the machine’s current state.
Using simulation-based analysis, the system determines how the machine structure would need to be adjusted to return to an aligned condition. The resulting outputs provide guidance on how support or fixation points should be adjusted, enabling more direct and informed corrective actions. By converting measurement data into alignment guidance through computational analysis, the method streamlines a traditionally time-consuming process. This approach reduces machine downtime, limits economic losses, and improves consistency in alignment outcomes without requiring changes to existing machine designs.
Benefits
- Reduces CNC machine downtime
- Minimizes trial-and-error alignment efforts
- Improves dimensional accuracy and consistency
- Decreases labor and operational costs
Applications and Industries
- CNC machining and manufacturing
- Precision manufacturing environments
- Machine tool maintenance and calibration
- Industrial equipment servicing
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
