What the data for this category looks like
The data for this category comes from electromagnetic design databases, copper wire and insulating material batch ledgers, winding equipment, balancing machines, electrical test benches, and ERP/MES systems. Daily documents include winding process cards, insulation treatment records, dynamic balance reports, withstand voltage insulation test records, and type and factory test reports. Data is updated per single motor, per product batch, or for each type modification. Document fields include winding turns, insulation class, dynamic balance deviation values, temperature rise test data, withstand voltage test parameters, and some parameters have physical units such as rotational speed, current, and insulation resistance values.
What constraints these characteristics impose on the deployment and upgrade phase
The inspection and maintenance Q&A for this category relies on exclusive process and test data for individual units or batches. When deploying, support must be provided for associating exclusive knowledge base fragments with batches. Data update frequency changes with production batches. During the upgrade phase, ensure that incremental knowledge base synchronization does not interrupt production workflows. Document fields include multi-dimensional physical parameters, so support must be provided for precise matching retrieval of numerical fields with units. It must also support structured and unstructured data from multiple sources, to avoid retrieval failures caused by cross-system data format conflicts.
How to configure the settings
These configurations are written based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
MONGODB_URI | Point to an internal enterprise 3-node replica set instance | Data for this category grows continuously with production batches; a replica set ensures read/write performance and data reliability |
REDIS_URL | Configure as a dedicated cache instance with 16 GB memory and 3600 second expiration time | Used to cache frequently retrieved process documents and test data to reduce database load |
DB_MAX_LINK | 100–150 | Matches the high concurrency of inspection requests at the workshop level, avoiding connection exhaustion |
FE_DOMAIN | Bind to a dedicated internal workshop domain name | Restrict access to the production department’s internal network to ensure data security |
STORAGE_S3_ENDPOINT | Point to an internal enterprise object storage address with 500 GB capacity | Used to store uploaded process documents and test reports for unified management |
Three common mistakes
- Infinite service restarts after startup, with database connection timeout shown in logs. The cause is incorrect configuration of
MONGODB_URIto point to the production environment database, or settingDB_MAX_LINKtoo low which causes connection pool exhaustion. - The knowledge base cannot sync structured ERP/MES data from the workshop. The cause is failing to configure
STORAGE_S3_ENDPOINTto adapt to the enterprise’s internal object storage, resulting in failed file uploads. - Search results cannot match the exact value of winding turns. The cause is not enabling structured field matching rules, and using only full-text search leads to insufficient parameter matching accuracy.
How to verify the configuration is complete
- Log in to the FastGPT backend to check database connection monitoring, and confirm that the current connection count is below the threshold set by
DB_MAX_LINK. - Upload a winding process card to the knowledge base, and verify that the document can be retrieved via keywords and return complete content.
- Initiate a test query containing "winding turns", and confirm that the returned results include the exact field data of the corresponding document.
- Perform a service restart operation, and observe that the process logs have no abnormal errors and the service runs stably.
The values provided are common starting points and should be measured against the reader's own samples.