Build a Plant Sensor Calibration and Spare-Parts Visit Scheduler

Cross-reference simulated open62541 sensor drift flags with enterprise spare parts catalogs. Formulate technician calibration service itineraries and spare sensor pick tickets.

Instrumentation Maintenance Coordinator

Ingest simulated open62541 OPC UA diagnostic nodes flagging analog sensor drift.

Cross-reference drifting sensors against enterprise warehouse stock for replacement probes.

Sequence calibration and replacement tasks based on plant physical zone adjacency.

Generate a technician service visit itinerary accompanied by warehouse pick tickets.

Plant zone schematic showing drifting sensors, stock availability indicators, and itinerary checklist.

Create synthetic normalized open62541 diagnostic records and spare parts inventory manifests in local JSON fixtures. Starter examples below are synthetic. They are not downloaded records.

open62541 OPC UA OPC UA instrumentation diagnostic structures and status code nodes from open62541.

pydantic-ai, fastapi, pandas. Pydantic AI guarantees rigid data validation when joining telemetry anomaly codes with parts catalogs. Instruction-tuned model capable of reliable multi-table matching and itinerary sequencing.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Identifies all sensors flagged with active calibration drift status codes.

Matches sensor replacement requirements with in-stock part SKUs.

Groups service visits by plant physical zone to minimize technician transit time.

```json [ { "input": { "sensor_diagnostics": [ { "sensor_id": "TEMP_TANK_1", "zone": "ZONE_NORTH", "drift_detected": true, "part_type": "PT100_PROBE" }, { "sensor_id": "PRESS_PIPE_4", "zone": "ZONE_NORTH", "drift_detected": true, "part_type": "4_20MA_TRANSMITTER" } ], "inventory": [ { "part_sku": "SKU_PT100", "part_type": "PT100_PROBE", "qty_on_hand": 5 }, { "part_sku": "SKU_PRESS_TX", "part_type": "4_20MA_TRANSMITTER", "qty_on_hand": 2 } ] }, "expected_output": { "scheduled_zone": "ZONE_NORTH", "pick_ticket": [ { "part_sku": "SKU_PT100", "quantity": 1, "target_sensor": "TEMP_TANK_1" }, { "part_sku": "SKU_PRESS_TX", "quantity": 1, "target_sensor": "PRESS_PIPE_4" } ], "itinerary_order": [ "TEMP_TANK_1", "PRESS_PIPE_4" ], "all_parts_available": true } }, { "input": { "sensor_diagnostics": [ { "sensor_id": "FLOW_METER_2", "zone": "ZONE_SOUTH", "drift_detected": true, "part_type": "MAG_FLOW_LINER" } ], "inventory": [ { "part_sku": "SKU_MAG_LINER", "part_type": "MAG_FLOW_LINER", "qty_on_hand": 0 } ] }, "expected_output": { "scheduled_zone": "ZONE_SOUTH", "pick_ticket": [], "itinerary_order": [], "all_parts_available": false } } ] ```

Advisory scheduling and pick ticket generation only. Warehouse inventory decrements and physical sensor swaps require human execution. Use mock external writes. Require human review before any real deployment.