What Data for This Category Looks Like
Data for this category comes from daily operational outputs of manufacturing enterprise equipment departments, workshop maintenance teams, and public utility departments. It includes documents such as equipment ledgers, inspection checklists, maintenance plans, work orders, fault analysis reports, spare parts lists, and special equipment inspection records. Data sources cover EAM/CMMS systems, device sensor data, operator inspection records, maintenance history, spare parts inventory, and statutory inspection information. Update frequencies include shift-by-shift inspections, daily/weekly/monthly maintenance plan updates, and immediate reporting when a fault occurs. Document fields include equipment number, inspection location, parameter value, exception threshold, work order number, fault description, processing duration, spare part model, inspection validity period, and other fields. Fields are adjusted flexibly based on document type.
Constraints for Deployment and Upgrade
Data for this category comes from multiple dispersed sources with varied update rhythms. During deployment, support scheduled synchronization of multiple data sources and real-time incremental data access. Ensure real-time performance of pre-shift inspection records and device sensor data. Ensure immediate reporting of work orders when a fault occurs. Document types and field structures vary widely. During upgrades, support parsing of multi-format documents and custom field mapping. Avoid missing key maintenance information in exception reports. Errors can directly lead to unplanned downtime or safety incidents. Strengthen data verification and permission control during deployment. Ensure compliance with access to sensitive documents such as special equipment inspection records. Maintenance windows must follow production scheduling. Reserve associated configuration interfaces for the knowledge base and production scheduling system during deployment. Ensure maintenance plans match production rhythms.
Configuration Settings
The configurations on this page apply to FastGPT v4.17.0
| Configuration Item | Recommended Value | Rationale for This Value |
|---|---|---|
MONGODB_URI | mongodb://admin:yourpass@host:27017/fastgpt_device?authSource=admin | Stores semi-structured document data such as equipment ledgers and fault analysis. Configure correct authentication information to ensure data access security |
PG_URL | postgresql://device_user:yourpass@host:5432/device_maintain | Stores structured data with time-series attributes such as inspection checklists and maintenance plans. PostgreSQL supports multi-field associated query requirements |
REDIS_URL | redis://:yourpass@host:6379/0 | Caches real-time device sensor data and pre-shift inspection records. Reduces database query pressure and supports high-frequency data access |
STORAGE_S3_ENDPOINT | Configure according to the enterprise’s internal object storage service address | Stores large-volume documents such as special equipment inspection records and spare parts lists. Adapts to the enterprise’s existing storage architecture |
DB_MAX_LINK | 20–50 | Data access peaks for this category occur during pre-shift inspections and fault reporting. Limit the number of connections to avoid exhausting database resources |
FILE_TOKEN_KEY | Random 32-bit string generated according to enterprise key management specifications | Protects access permissions for sensitive documents such as uploaded inspection records and maintenance work orders. Prevents unauthorized access |
Three Common Misconfigurations
- Symptom: Different nodes cannot share inspection records and maintenance work order data after multi-node deployment. Cause:
STORAGE_S3_ENDPOINTorREDIS_URLis not configured correctly to enable cross-node data synchronization and storage. - Symptom: Device documents cannot be accessed normally after enabling team management functionality in a local deployment. Cause: Permission verification fails because
FILE_TOKEN_KEYorROOT_KEYis not configured correctly. - Symptom: Spare parts inventory fields are missing from exception reports generated when a fault occurs. Cause: The spare parts list table from the EAM data source is not correctly associated with the knowledge base document parsing rules, resulting in incomplete field mapping.
How to Verify Successful Configuration
- Access the domain configured in
FE_DOMAIN. After logging into the system, check whether the equipment ledger list loads normally, with no loading failure prompts. - Upload a paper inspection checklist scan or electronic inspection checklist document. Verify that the parsed content includes required fields such as inspection location, parameter value, and exception threshold.
- Trigger a simulated fault reporting process. Check whether the generated exception report is associated with the corresponding work order and spare parts list data.
- View background system logs. Confirm that the connection status of
MONGODB_URI,PG_URL, andREDIS_URLis normal, with no timeout or authentication failure errors.
These values serve as common starting points and should be validated against the specific samples of the deployment environment.