PROBLEM
Factory challenge
Brownfield data is isolated and responsibility between AI and safety control is unclear.
C · CONTROL
Physical AI Control
Connect AI prediction and optimization while preserving the authority of safety PLC and motion control.
APPROACH
OPTO approach
Use EdgeLink, PredictCare and TwinForge for protocol integration, anomaly signals and virtual FAT.
SOLUTIONS
Representative solutions
Safe AI action and data access for brownfield equipment
EdgeLink
Brownfield protocol, data and AI gateway
Connects legacy PLCs, sensors and upper-level systems while keeping write authority, timing and safe-state responsibilities explicit.
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PredictCare
Sensor-based anomaly detection and asset health
Detects changes in vibration, current, temperature and pressure signals and supports maintenance decisions with operating-context evidence.
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TwinForge
SIL/HIL, synthetic data and virtual FAT
Validates control logic, robot missions and data interfaces in a virtual environment before they are introduced to the production line.
Learn morePROOF & DELIVERABLES
Verification deliverables that remain
Acceptance is based on the documents, data and procedures needed for approval and operation.
- 01I/O and protocol map
- 02Safety and control responsibility boundary
- 03SIL/HIL test package
- 04Alarm and anomaly criteria
- 05Change and recovery runbook
INTEGRATION
Integration scope
- PLC and motion systems
- Industrial sensors
- MES and SCADA
- ROS 2 and robots
- Network and identity services
CONTROL
Design a verification path for your site
Specifications and performance are agreed through sample and site-specific PoC gates.