01Observed
Real mill scan
Field point-cloud observation
54,730,187Original scan points
domestic-sagSAG / SPATIAL DATA
Loading real point-cloud model
Real point clouds · Spatial liner state
Building the digital sensing layer for automated mineral processing plants
We turn real mill scans into structured spatial liner state so geometric change becomes computable and traceable.
Real point-cloud process replayRaw scan
01 / 08Raw scan
Real field observations and surroundings enter view
Raw scan · Real field observations and surroundings enter view00 / 40s
data path
One traceable data path
OBSERVATION TO SPATIAL RECORD
Observed
Open this cell's real caseA real field observation from a SAG mill at a domestic mine, with its source and spatial context retained.
evidence / 01
A real scan now resolves into reviewable spatial results
Every number below comes from the same anonymous case evidence. It proves an operating workflow, not certified metrology or cross-machine accuracy.
8.500 mNominal shell inner diameter
3.800 mNominal barrel length
213 m³Nominal effective volume
13.100757%New-liner scan filling
10.328186%Operating scan filling
43 / 72Comparable spatial cells
Spatial Liner Cell01 · Real case
Move from a full mill scan into one spatial liner cell
Follow the physical axis toward the shell, overlay the new-liner and operating scans inside shared coverage, then inspect the profile and spatial difference.
An Anonymous SAG Mill at a Domestic Mine
View the real case 02 · Data infrastructure
Build the reusable spatial object before building the model
Each Spatial Liner Cell carries time, coordinates, geometry, relative change, coverage, and evidence boundaries. That traceable object can later support simulation and liner-wear machine learning.
View the data path- 01
Real scans
54.7MField observation points
- 02
Spatial cells
43Comparable cells with shared coverage
- 03
Periodic structure
92.6%θ-z coverage
- 04
Model data foundations
AI-readySimulation and ML · Future direction