Manufacturing Ontology
Comprehensive domain knowledge for manufacturing and production operations.
Overview
The Manufacturing ontology provides AI agents with deep understanding of:
- Production planning and scheduling
- Quality control and assurance
- Materials and inventory management
- Equipment maintenance and operations
- Supply chain coordination
Key Entities
| Entity | Description | Attributes |
|---|---|---|
| Product | Manufactured item | SKU, BOM, Specs, Status |
| Work Order | Production job | Quantity, Priority, Status, Schedule |
| Material | Raw material | Part Number, Quantity, Location |
| Equipment | Production asset | ID, Type, Status, Maintenance |
| Quality Check | Inspection | Type, Result, Defects, Date |
Common Workflows
Production Cycle
graph LR
A[Work Order] --> B[Material Check]
B --> C{Available?}
C -->|Yes| D[Production]
C -->|No| E[Purchase]
D --> F[Quality Check]
F --> G[Packaging]
Preventive Maintenance
- Equipment monitoring
- Maintenance scheduling
- Parts inventory management
- Downtime minimization
- Performance tracking
Regulatory Compliance
| Regulation | Scope | Key Requirements |
|---|---|---|
| ISO 9001 | Quality management | Process controls, documentation |
| OSHA | Workplace safety | Equipment guards, training, PPE |
| EPA | Environmental | Emissions, waste management |
| FDA | Food/pharma | GMP, validation, traceability |
Prompt Templates
Production Planning
Create production schedule:
- Orders: {order_backlog}
- Capacity: {available_hours}
- Materials: {inventory_status}
- Constraints: {equipment_downtime}
Optimize schedule for on-time delivery while
minimizing changeovers and maximizing efficiency.
Quality Issue Analysis
Analyze quality issue:
- Product: {product_id}
- Defect: {defect_description}
- Batch: {batch_number}
- Occurrence rate: {defect_rate}
Identify root cause, recommend corrective actions,
and suggest preventive measures based on quality data.
This ontology is continuously updated based on manufacturing standards and industry 4.0 practices.