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Build a Production Lot Genealogy and Recall Rehearsal Engine — implementation
Linked challenge: Build a Production Lot Genealogy and Recall Rehearsal Engine
Prompt source
implementation88 lines11 sectionsNo variables1 code block
## Build
Trace serialized component consumption across sub-assemblies by parsing open62541 OPC UA lot tracking nodes. Generate containment blast-radius reports and supplier recall rehearsal dossiers for quality compliance teams.
## User
Quality Assurance Manager
## Workflow
1. Ingest simulated OPC UA node variable hierarchies detailing component lot bindings and parent sub-assemblies.
2. Traverse upstream and downstream parent-child lot relations to map the complete production genealogy tree.
3. Calculate the defect blast radius given a simulated quarantine lot identifier.
4. Generate a structured recall rehearsal packet specifying quarantined serialized units and warehouse locations.
## Interface
Genealogy graph explorer showing forward and reverse lot relationships, affected item totals, and quarantine export tables.
## Data
Simulated multi-tier bills of materials and lot binding records provided as JSON fixtures matching open62541 variable schemas.
Starter examples below are synthetic. They are not downloaded records.
## Source
[open62541 OPC UA](https://raw.githubusercontent.com/open62541/open62541/master/README.md)
OPC UA information model node attributes and variable browse paths from open62541 core node storage.
## Tools
langgraph, pydantic, networkx.
Manages cyclic parent-child lot traversal graph state and recursive genealogy tree expansion.
Structured LLM capable of generating clean compliance audit reports from nested JSON trees.
## Deliverables
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.
## Acceptance
- Traverses multi-level lot trees up to 5 tiers without cycle deadlocks.
- Identifies 100% of downstream units associated with a designated bad lot.
- Outputs ISO 9001 audit-compliant containment action plans in structured JSON.
## Starter Examples
```json
[
{
"input": {
"quarantined_lot": "LOT-STEEL-402",
"genealogy_records": [
{
"lot_id": "LOT-STEEL-402",
"parent_subassembly": "SUB-CHASSIS-11",
"station": "ST_PRESS_01"
},
{
"lot_id": "SUB-CHASSIS-11",
"parent_subassembly": "FINAL-VEHICLE-8801",
"station": "ST_FINAL_02"
},
{
"lot_id": "SUB-CHASSIS-11",
"parent_subassembly": "FINAL-VEHICLE-8802",
"station": "ST_FINAL_02"
}
]
},
"expected_output": {
"quarantine_id": "LOT-STEEL-402",
"impacted_subassemblies": [
"SUB-CHASSIS-11"
],
"impacted_final_units": [
"FINAL-VEHICLE-8801",
"FINAL-VEHICLE-8802"
],
"containment_action": "HOLD_SHIPMENT"
}
},
{
"input": {
"quarantined_lot": "LOT-RESISTOR-99",
"genealogy_records": [
{
"lot_id": "LOT-RESISTOR-99",
"parent_subassembly": "PCB-MOD-01",
"station": "ST_SMT_04"
}
]
},
"expected_output": {
"quarantine_id": "LOT-RESISTOR-99",
"impacted_subassemblies": [
"PCB-MOD-01"
],
"impacted_final_units": [],
"containment_action": "QUARANTINE_WIP"
}
}
]
```
## Safety
Operates strictly in an offline rehearsal mode on historical lot logs without triggering physical warehouse lockouts.
Use mock external writes. Require human review before any real deployment.