# LK Revises L100NX Scanner Accuracy Figures—What the Numbers Mean https://cncoutlook.com/news/lk-l100nx-laser-scanner-accuracy-update/ By CNC Outlook Editorial · 2026-10-21 LK's October L100NX improvement changes published form error, point dispersion and dimensional accuracy; these separate metrics should not be conflated. LK Metrology has revised three published figures for its [L100NX]() scanner: form error from 15 to 10 micrometres, point-cloud dispersion from 26 to 16 micrometres, and dimensional accuracy from 20 to 15 micrometres. The figures are specific, but they describe different measurement properties. These numbers describe different behaviours. Form error concerns how faithfully measured data represents a reference shape. Point-cloud dispersion describes the scatter of individual points, which affects the noise an analyst sees during fitting or comparison. Dimensional accuracy addresses the deviation of a determined dimension from its reference value under the stated measurement conditions. A lower dispersion figure does not by itself establish better dimensional accuracy. Software filtering can make a point cloud look smoother without improving the relationship between the measured surface and its true geometry. Likewise, the scanner's performance depends on the CMM, mounting, calibration, measurement path and surface being scanned. Measurement uncertainty is not the same as the nominal accuracy number on a sensor brochure. When an L100NX scanner is mounted to a coordinate measuring machine, the combined system has error contributions from axis geometry, motion, environmental conditions and the sensor's calibration. The uncertainty associated with a fitted hole or edge depends on how those errors interact with the scan strategy. A part tolerance should be compared with the uncertainty of the final measurement method rather than one component's published specification. Cleaner point clouds and more accurate measured dimensions are related, but they are not interchangeable claims. ## A sensor number is not a full measurement uncertainty budget The L100NX can be used with LK machines and is also marketed for retrofit applications on compatible CMMs. For a workshop upgrading an existing inspection setup, this broadens the decision beyond buying a new measuring machine. But installation on another CMM may require software, controller and calibration changes that affect the final performance. Shops should be particularly cautious with measurements derived from sparse or difficult surfaces. A clean scan of a flat reference artifact may not predict performance on an oily, steeply angled or highly reflective component. The most useful qualification uses a reference part with the same feature types and finishes as real production, compares repeated results over several runs and records the measurement strategy. The revised LK numbers are meaningful inputs to that process, but they are not a substitute for it. Machined components rarely present ideal optical surfaces. Reflective edges, deep pockets and steep walls can reduce accessible data or complicate registration. A realistic evaluation should compare representative materials and finishes, verify a master component and document repeatability across multiple operators or measurement routines. The revised accuracy figures may help users assessing tight-tolerance inspection, especially where scan-based feature measurement is increasingly important. Yet the drawing tolerance and the uncertainty budget must still determine whether optical scanning is appropriate; nominal sensor specifications cannot replace the inspection method. The revised L100NX specifications provide a concrete basis for comparison. They become useful to a CNC inspection team only after a reference part shows whether the complete scanner-and-CMM configuration can measure the particular tolerances reliably. ## Sources & References - [LK L100NX Scanner Receives Improved CMM Accuracy Specification]() — Metrology and Quality News (2026-10-21T12:00:00Z) © CNC Outlook. See https://cncoutlook.com/terms/ for reuse terms.