Solutions · Physical AI
AI that sees the plant floor.
Machine vision, robotics, sensors and MES events land on the same knowledge graph as orders, BOM and suppliers, so what happens on the line changes the plan straight away instead of sitting in a separate dashboard.
What is physical AI?
Physical AI is artificial intelligence that perceives and acts in the physical world through cameras, sensors, machines and robots, rather than only working on documents and spreadsheets. In a plant it covers machine vision inspection, robotic cells, equipment health and line telemetry. ExlAthena connects those signals to planning so they change decisions, not just dashboards.
What you get
- Machine vision and quality-inspection signals in the plan
- Robotics and line telemetry linked to orders and BOM
- Yield, scrap and downtime events traced to customer impact
- Predictive maintenance and remaining useful life built in
- Explainable next-best actions with planner approval
- Edge or on-network processing for sensitive plant data
How it works
How ExlAthena physical AI works
- 01
Perceive
Camera, vision-inspection, robot-controller, PLC and IoT sensor streams are read alongside MES events such as yield, scrap and downtime.
- 02
Interpret
Signal processing and anomaly detection turn raw readings into events the business understands, for example a yield drop on Line 3 or a robot cell slowing down.
- 03
Connect
Each event is linked on the knowledge graph to the asset, the work order, the BOM, the SKU and the customer orders it affects.
- 04
Recommend
The decision engine proposes the next best action, such as re-sequence, switch line, hold a batch or raise a spare-part order, with its OTIF, cost and capacity impact.
- 05
Approve and write back
A planner approves, and the change is written back to ERP or MES so the next run measures what actually happened.
Supply chain impact
Why physical AI belongs in supply chain planning
Yield drives supply
A falling first-pass yield means fewer good units. ExlAthena adjusts available supply and flags the orders that will run short.
Line events change capacity
A slowed robot cell or a stopped line updates available capacity, so sequencing and promise dates follow reality.
Quality protects customers
A vision-detected defect pattern can hold the affected batch and trace which shipments and customers are exposed.
Answers
Physical AI questions, answered
What is physical AI?
Physical AI is artificial intelligence that perceives and acts in the physical world through sensors, cameras, machines and robots. In manufacturing it includes machine vision inspection, robotics, equipment health monitoring and line telemetry.
How is physical AI used in manufacturing?
Common uses are machine vision quality inspection, robotic picking and assembly, predictive maintenance of equipment, and real-time monitoring of yield, scrap and downtime. ExlAthena connects these signals to production and supply chain planning.
What is the difference between physical AI and generative AI?
Generative AI creates text, images or code from data. Physical AI senses and acts on real equipment and environments. ExlAthena uses physical AI signals as inputs and adds natural-language questions on top, so planners can ask why a line changed the plan.
How does physical AI connect to supply chain planning?
ExlAthena places shop-floor events on a knowledge graph with orders, BOM, routing, capacity and suppliers. A yield drop or line stoppage then updates supply, capacity and promise dates and produces a recommended action for approval.
Do we need new sensors or robots to use ExlAthena physical AI?
Usually not. ExlAthena starts with the vision systems, PLCs, historians, MES and IoT sensors the plant already has, and adds coverage where a gap blocks a decision.
Is physical AI data processed on site?
It can be. ExlAthena supports edge and on-network processing for sensitive plant data, with only the decision-relevant results shared with the planning layer.
Is predictive maintenance part of physical AI?
Yes. Predictive maintenance is one of the most common physical AI use cases. ExlAthena includes remaining useful life prediction, anomaly detection and maintenance optimisation as part of its physical AI module.
Who approves actions that physical AI recommends?
A planner or plant leader. ExlAthena proposes the action with its signals, model and expected impact, and nothing executes without approval unless your policy explicitly allows it for low-risk cases.
Next step
See Physical AI on your own plant data
A discovery workshop on live ERP, MES and asset data shows where the first decision pays back.