What data for this category includes
This category covers operation and maintenance records across the full lifecycle of manufacturing enterprise equipment. Data sources include EAM/CMMS systems, device sensor data, operator point inspection records, maintenance history archives, spare parts inventory lists, and statutory inspection documents. Data update rhythms include shift-based point inspection submissions, weekly maintenance plan distribution, and real-time reporting when faults occur. Daily documents include standardized equipment ledgers (with equipment number and installation location fields), point inspection forms (with inspection items, measured values, and qualified thresholds), maintenance work orders (with fault description and handling measures), spare parts lists (with model and inventory quantity), and special equipment inspection records. Most data fields are equipment-related physical quantities and operation records. Units include millimeters, degrees Celsius, hours, and other standard units.
Constraints imposed during deployment and upgrade
Multi-source heterogeneous data sources require support for multi-format data access and structured parsing during deployment. This must adapt to EAM/CMMS database formats and device sensor time-series data formats. High-frequency update rhythms require proper configuration of database connection pools and index refresh strategies. This prevents data synchronization delays from disrupting shift-based point inspection and maintenance acceptance workflows. Diverse document types and compliance requirements require support for dedicated storage paths for statutory inspection records. This ensures data traceability. Upgrade processes must maintain service availability during production hours. Rollback mechanisms must be configured to avoid interrupting core equipment operation and maintenance workflows during upgrades. The complex business logic tied to data requires field mapping configuration before deployment. This ensures accurate alignment between point inspection items and maintenance work order fields.
Configuration settings
The following configuration items are based on the standard deployment process for FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://admin:pass@internal-db:27017/cmms_data?authSource=admin | Connects to equipment ledger and maintenance work order data stored in EAM/CMMS systems |
PG_URL | postgresql://maintain_user:pass@internal-pg:5432/device_ops?schema=inspection module | Stores structured point inspection forms, maintenance plans, and spare parts inventory data |
REDIS_URL | redis://:redis_pass@internal-redis:6379/1 | Caches frequently accessed point inspection items and spare parts lists to reduce database concurrency pressure |
DB_MAX_LINK | 20–30 | Adapts to concurrency connection requirements for multiple data sources, prevents connection exhaustion during production hours |
STORAGE_S3_ENDPOINT | http://internal-storage:9000 | Stores device sensor logs and statutory inspection records to meet compliance storage requirements |
Three common configuration errors
- A MongoDB connection timeout error (status code 104) occurs after deployment. The cause is incorrect configuration of authentication parameters in
MONGODB_URI, and failure to specify the database namespace where EAM/CMMS data is stored. - Point inspection data synchronization delay exceeds 30 minutes after an upgrade. The cause is failure to adjust the
DB_MAX_LINKparameter; insufficient concurrent connections causes a blockage in the data synchronization queue. - Access to LAN-based CMMS data interfaces fails. The cause is failure to configure
FE_DOMAINas the internal network domain name, leading to blocked cross-domain access.
How to confirm configuration is complete
- The built-in database connectivity test script is executed to verify normal connection status for
MONGODB_URIandPG_URL. - A standard point inspection form document is uploaded to confirm correct parsing and synchronization to the corresponding structured data table.
- A simulated fault reporting operation is triggered to confirm data index updates are completed within the preset time frame.
- The specified storage node is checked to confirm statutory inspection records have been uploaded and stored according to configuration.
The values provided are common starting points and should be measured against the reader's own samples.