What Data for This Category Looks Like
Daily documents for this category include assembly process cards, BOM lists, torque records, gap adjustment records, commissioning reports, factory inspection sheets, and packing lists. Data sources include PLM/ERP systems, part inspection data, assembly tool collection records, test bench data, MES systems, and customer technical agreements. Data is updated once per device or per order. Fields include part number, torque value, gap parameters, inspection results, and more. Common units are newton meters, millimeters, pascals, and other physical quantities.
Constraints Imposed by These Characteristics on Deployment and Upgrade
Since data for this category is updated per order or device and linked to multi-level BOM structures, deployment must reserve dynamic access interfaces for multi-source heterogeneous data. It must also adapt to data formats from systems such as PLM and MES. Real-time collected data such as torque and gap values during assembly has strict timeliness requirements. Deployment must configure low-latency data synchronization links. Daily documents include multiple types of structured and unstructured content. When upgrading the knowledge base, parsing rules must be adapted for different formats such as assembly process cards and factory inspection sheets. The multi-variant, order-based assembly feature requires the deployed system to support order-level data isolation. This prevents mixing of assembly data from different batches.
Configuration Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 | Adapts to concurrent query demands for multiple assembly documents per order, and prevents database connection exhaustion |
MONGODB_URI | Points to a dedicated database instance storing assembly BOMs and inspection records | Isolates equipment assembly business data from other business data to ensure query efficiency |
REDIS_URL | Configured as the address of a local cache cluster | Caches frequently queried assembly process cards and torque threshold data to reduce database load |
STORAGE_S3_ENDPOINT | Points to the enterprise internal object storage service address | Stores unstructured documents such as test bench videos and scanned files from the assembly process |
ROOT_KEY | Generated per enterprise permission management rules | Controls highest-level access to the system backend to prevent unauthorized operations |
PG_URL | Points to a relational database storing work orders and customer technical agreements | Supports transactional query demands for structured work order data |
Three Common Configuration Mistakes
- Symptom: For FastGPT deployed via Docker, the model backend receives response logs, but workflow conversations display a failure. Cause:
FILE_TOKEN_KEYis not configured, or the key does not match. This prevents the workflow from passing context data from model responses. - Symptom: After deploying a 16B model, answer wait time exceeds 3 minutes. Cause: The
DB_MAX_LINKconfiguration is not adjusted. Insufficient database concurrent connections cause data query delays, which extend the model response cycle. - Symptom: After upgrading from v4.9 to v4.12.2, existing assembly work order data is lost. Cause: Only the docker-compose file is updated, and no persistent storage volume is mounted. Database data is not retained alongside the container.
How to Verify Successful Configuration
- Run a multi-source data access test to confirm that BOM and torque data from PLM and MES systems can be synchronized to the system normally. Verify that data fields match business documents.
- Submit a simulated assembly work order to trigger a quality traceability query. Confirm the system returns all assembly records and inspection reports for the corresponding order.
- Initiate a model inference test to confirm responses meet business scenario requirements. Adjust configurations until expected outcomes are achieved.
- Run a version upgrade verification to confirm that business data is not lost during the upgrade, and that the service starts normally.
The values provided are common starting points and should be measured against the reader's own samples.