All Industries

Advanced Manufacturing

Smart factory OT/IT convergence, predictive maintenance, and digital twin platforms for tier-1 industrials.

OT/IT convergence with visual stack design and governed plant data.

Advanced Manufacturing — platform view
Advanced Manufacturing — platform view
// Case studies

How the platform and products create value here.

Case 01 / Tier-1 automotive supplier

Plant stacks designed visually, deployed identically

Cloud PlatformMicroServicesOpsSecretOps
Challenge
Each plant's MES/historian stack drifted apart after years of manual edits, so a fix validated in one plant broke in the next.
Approach
Teams model the plant stack in the Container Visual Designer, edit the generated Docker Compose in place, and roll the same definition to every site with environment overrides.
9
plants on one stack definition
-60%
config drift incidents
Days → hours
new line bring-up
Drag-and-drop container map for the full plant stack.
Drag-and-drop container map for the full plant stack.
Drag-and-drop container map for the full plant stack.
Compose and environment variables edited alongside the visual model.
Compose and environment variables edited alongside the visual model.
Compose and environment variables edited alongside the visual model.
Case 02 / Precision components manufacturer

Vision inspection data as a governed data product

Data PlatformDataspace
Challenge
Inspection imagery piled up in per-line NAS shares. Retraining a defect model meant weeks of hunting for labeled frames.
Approach
Imaging is stored as multi-dimensional arrays in Dataspace with lineage from raw capture to training view, queryable by SQL and consumable by quality dashboards.
3 weeks → 1 day
training set assembly
+11 pts
defect recall after retraining
Full
capture-to-model lineage
Imaging pixels modeled as height × width × channel arrays.
Imaging pixels modeled as height × width × channel arrays.
Imaging pixels modeled as height × width × channel arrays.
Node metadata shows exactly which capture feeds which training view.
Node metadata shows exactly which capture feeds which training view.
Node metadata shows exactly which capture feeds which training view.

Smart Factory OT/IT Convergence

ManufacturingIndustry 4.0MES

Smart Factory OT/IT Convergence

Decades of OT investment sit behind air gaps. CYBERIA bridges that divide safely — exposing line-level telemetry to enterprise analytics while preserving the deterministic control loops that keep production running.

Outcomes

  • 15–30% improvement in OEE through real-time bottleneck detection
  • AI-driven defect detection at line speed using edge inference
  • Mean-time-to-resolution cut by 60% via root-cause copilots