IIoT / EDGE
Industrial data architecture
Define namespace, timestamps, units, quality, MQTT topic structure, OPC UA information models, buffering, and store-and-forward behavior before analytics.
LAB 01Advanced workshop series
IIoT, digital twin & EOAT robotics
Three connected workshop tracks for converting machine behavior into trustworthy data, testing control systems against useful models, and deploying maintainable robot cells.
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MODEL / TEST
Digital twin & virtual commissioning
Connect physics, sequence, controller emulation, I/O simulation, calibration evidence, and model validity limits to a repeatable commissioning workflow.
LAB 02ROBOT / CELL
Robotics & EOAT engineering
Validate payload inertia, reach, singularities, grip force, utility routing, cycle time, guarding, safety functions, maintenance access, and recovery.
LAB 03Shared engineering thread
All three workshops depend on explicit semantics. The physical machine must expose signals with known meaning; the model must state what it represents and where it is invalid; and the robot cell must express production states, faults, and recovery actions consistently. Without those definitions, connectivity adds data but not operational knowledge.
Workshop artifact set
- Architecture and trust-boundary diagram
- Signal or tag dictionary with units, quality, and ownership
- Model assumptions and validation record
- Normal, faulted, maintenance, and recovery state definitions
- Acceptance criteria tied to measurable evidence