UA-.NETStandard/samples/Vision/VisualInspectionAgent

Visual Inspection Agent

VisualInspectionAgent is the external deterministic orchestrator for the VisualInspectionCell server. It uses typed OPC UA clients for Vision, AI Model Management, ISA-95 Job Control V2, and Alarms & Conditions; it does not call server internals.

The model path never owns the production verdict. The agent captures a fixture image, measures characteristics, routes the measurements through the AI companion deployment's Invoke method for provenance, and then applies the recipe rule locally before touching job control.

flowchart TD
    Start["Start cycle"] --> Capture["Get fixture PNG from FixtureImages"]
    Capture --> Measure["Measure BoreDiameter, SlotWidth, EdgeOffset"]
    Measure --> Invoke["Call deployment Invoke for provenance"]
    Invoke --> Judge["Apply deterministic recipe rule"]
    Judge --> Decision{"Verdict"}
    Decision -->|"Ok"| CompleteOk["Complete and close inspection job"]
    CompleteOk --> NextInspection["StoreAndStart VIS-INSP-BRACKET-001"]
    Decision -->|"NotOk"| CompleteBad["Complete and close inspection job"]
    CompleteBad --> Rework["StoreAndStart VIS-REWORK-REJECT-001"]
    Decision -->|"NotDecidable"| Hold["Hold for operator dialog"]
    Hold --> Correction["Submit ground-truth correction"]

Running

Start the cell first:

dotnet run --project samples\Vision\VisualInspectionCell\VisualInspectionCell.csproj -- --insecure

Then run the agent:

dotnet run --project samples\Vision\VisualInspectionAgent\VisualInspectionAgent.csproj -- --server opc.tcp://localhost:62865/VisualInspectionCell --insecure --mode scripted --cycles 3

Options

Option	Meaning
--server <url>	Server endpoint. Default opc.tcp://localhost:62865/VisualInspectionCell.
--insecure	Demo-only certificate convenience.
--mode scripted|live-ai|human	Selects the operator/model mode. Default scripted.
--cycles <n>	Number of fixture cycles. Default 3, minimum 1.
--operator-timeout <seconds>	Bounded human wait. Default 10, minimum 1.
--ai-endpoint <uri>	Required for live-ai.

Exit codes

Code	Meaning
0	The requested cycles ran to completion.
2	The command line was rejected, for example an unknown --mode or live-ai without --ai-endpoint. No session is opened and no job is created.
3	The cell refused the run, for example an ISA-95 ReturnStatus that is not success, or a deployment that cannot serve live-ai. Reported as a single diagnostic line, not a stack trace.

Mode names are matched without regard to case, hyphens or underscores, so live-ai, live_ai and LiveAI are the same mode. An unrecognised mode is rejected rather than quietly treated as scripted, because a silent downgrade would run the simulated analyser while the operator believed a real model was deciding.

Modes

• scripted — the unattended path. The analyser and operator disposition are deterministic, and --cycles N makes the run finite.
• live-ai — requires --ai-endpoint. If no endpoint is configured, the agent exits before creating any ISA-95 job. There is no silent fallback to the simulated analyser, because a silently degraded sample appears to work while demonstrating nothing.
• human — waits for a real dialog subscriber for a bounded time. A timeout stops or holds; it never auto-approves and never blocks forever.

Job policy

Quality and job execution state are separate facts. A defective part does not mean the inspection job failed.

Verdict	Inspection job	Next job
Ok	complete, close	schedule next inspection
NotOk	complete, close	schedule rework/reject order
NotDecidable	hold	none until the operator answers

Scheduling chooses from the fixed catalogue exposed by the cell and calls ISA-95 V2 StoreAndStart. The agent never invents a job-order payload outside that catalogue.

Operator feedback and learning

For NotDecidable, the agent responds to OperatorDispositionDialog and sends Vision feedback with VisionFeedbackPurposeEnum.GroundTruthLabel. An accepted positive correction carries the measured characteristics. An accepted negative example uses the RetractAll path. The same correction is submitted twice in the current orchestrator to demonstrate that the cell counts a learning sample idempotently per stable sample id.

Related docs

• Vision developer guide — see Visual inspection: a cross-companion cell
• VisualInspectionCell
• Vision developer guide
• AI Model Management developer guide
• ISA-95 developer guide