← Solution examplesManufacturing example · MES ↔ QMS ↔ ERP
Quality Containment & Lot Genealogy
Quality knows something failed. MES knows how it was made. ERP knows where it went. We connect the chain before the problem becomes bigger.
solution / quality-containment
Engineering blueprintLAYER 01Existing systemsIntegrated, not replaced
ERPMESQMSSCADA / historianWMSMaintenance
LAYER 02Governed production dataCanonical, with lineage
LotsOrdersMachine runsQuality eventsShipments
LAYER 03KBSIntel containment layerGenealogy & orchestration
Genealogy graphHold triggersEvidence packages
LAYER 04Decisions & intelligenceBuilt on governed data
Containment scopeSupplier riskRepeat NCR causes
01
Problem
When a lot fails, the material, machine, process window, related lots, and shipments each live in a different system. Teams rebuild the chain by hand while suspect product keeps moving.
02
Example
A finished lot fails tolerance. Quality needs the supplier lot, machine run, related lots, open inventory, and shipped customers. Today that takes days.
03
Governed object · Production Lot
- Supplier lot
- Raw material
- Production order
- Machine run
- Finished lot
- Pallet
- Shipment
- Customer
04
Where the systems disagree
- Broken genealogy
- Missing process context
- Shipped suspect product
- Inconsistent quality codes
- Siloed maintenance
- Supplier data in PDFs
05
What we build
A genealogy and containment layer across MES, QMS, ERP, and WMS.
- Lot genealogy from supplier to customer
- Identifier mapping across MES, WMS, and ERP
- Process-window capture from historian data
- Automated containment and inventory holds
- Evidence packages for quality and customers
06
Controls
- Automated containment on quality events
- Holds on suspect lots across warehouses
- Related-process-window detection
- Customer impact list from shipped genealogy
07
Intelligence
- Supplier-risk patterns
- Repeated NCR root causes
- Good-versus-failed lot comparison
- Defect trends by line and material
08
What we'd measure
- Time from quality event to containment
- Suspect product shipped after an event
- Lots with complete genealogy
- Repeat NCRs by root cause
Start with one problem. Engineer the right solution.
Manual work, systems that don't talk, data nobody trusts. We trace it to the source and ship the fix into production.