What data for this category looks like
This category covers the entire forging workflow. Data sources include raw material quality certificates, heating furnace systems, press collection data, MES systems, non-destructive testing equipment, and customer forging drawings. Daily documents include forging process specifications, cutting cards, heating furnace logs, forging process cards, mold life records, heat treatment work orders, and ultrasonic testing reports. Fields include furnace batch numbers, forging ratios, heating temperatures, pressure parameters, defect types, and more. Data updates occur per piece, per batch, or per furnace run. A single data entry links to multiple stages of production records and testing results.
Constraints imposed by these characteristics during deployment and upgrade
This category of data has multi-source associations and high update frequencies. During deployment, support for batch docking of multiple data sources is required to avoid single-node processing bottlenecks. Daily document fields include professional parameters such as furnace batch numbers, forging ratios, and heating temperatures. Structured data mapping rules must be configured to retain original units and process association relationships. A single data entry links to multiple stages of records. During deployment, optimize the index structure to ensure batch traceability query efficiency. During upgrades, compatibility with the association logic of historical furnace batches and forging batches is required to avoid data gaps. At the same time, adapt to the storage and network environment of the workshop intranet to ensure stable data transmission.
How to set configurations
The configurations on this page apply to FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 200–300 | Adapt to concurrent requirements for batch access of multi-source data, match the data submission volume per furnace run in forging workshops |
MONGODB_URI | mongodb://username:password@host:port/fastgpt_forging?authSource=admin | Store unstructured documents such as ultrasonic testing reports and forging process cards, support multi-batch data archiving |
PG_URL | postgresql://username:password@host:port/fastgpt_forging_struct | Store structured data such as furnace batch numbers, forging ratios, and pressure parameters, ensure batch association query efficiency |
REDIS_URL | redis://:yourpassword@host:port/0 | Cache frequently queried heating furnace temperature and mold life data, reduce database access pressure |
STORAGE_S3_ENDPOINT | Configure according to workshop intranet storage nodes | Store batch-uploaded documents such as process specifications and heat treatment work orders, adapt to intranet access restrictions |
Three common mistakes
- Phenomenon: A 401 status code is returned when running a curl command to submit forging batch data. Cause: The
ROOT_KEYparameter is not configured correctly, causing interface authentication failure. - Phenomenon: Empty furnace batch number fields appear when batch importing ultrasonic testing reports after an upgrade. Cause: Structured data mapping rules are not configured, and the association fields between original testing reports and forging batches are not retained.
- Phenomenon: Timeouts occur when querying heating furnace historical data in batches after deployment. Cause: The
DB_MAX_LINKparameter is not adjusted, and insufficient concurrent connections cause request queuing and backlog.
How to confirm configurations are correct
- Run an authentication interface test, pass the configured
ROOT_KEY, and verify that the interface returns a normal response. - Import a single heating furnace record, check whether original fields such as heating temperature and furnace batch number are fully retained in the database.
- Submit a batch of forging process card files, check whether the storage service receives them normally and generates archive records.
- View database connection monitoring metrics, confirm that concurrent connections do not exceed the upper limit set by the
DB_MAX_LINKconfiguration.
The values provided are common starting points and should be measured against the reader's own samples.