What the data for this category looks like
Data originates from slab or billet batches, heating furnaces, mill automation control systems, online thickness and width measuring equipment, surface inspection devices, and manufacturing execution systems (MES). Records are generated upon completion of each coil or individual steel product. Critical parameters including thickness, temperature, and surface defect status are updated in real time. Daily documents include rolling plans, heating schedules, rolling specifications, flatness and thickness records, surface quality reports, and product quality certificates. Fields covered include batch numbers, geometric dimensions, process parameters, defect types and grades. No non-business fictional statistical data is included.
What constraints these characteristics impose during deployment and upgrade
Data for this category is generated per coil or individual steel product, and updated in real time. It requires associated batch traceability logic. During deployment, adapt to high-frequency, small-batch data writes. During upgrades, ensure the batch association link is not interrupted. Daily documents include multiple types of process and quality records. Deployment must support multi-format document parsing and accurate field mapping. The real-time parameter update requirement will limit vector database write latency. During upgrades, verify the stability of the data synchronization link. The strong correlation of coil-level traceability requires accurate configuration of association rules during deployment, to avoid batch data misalignment that impacts subsequent audit processes.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–200 concurrent connections | Adapts to the concurrent write demand of per-coil/per-piece data, and prevents database connection exhaustion |
STORAGE_S3_ENDPOINT | Points to the enterprise internal object storage node | Stores rolling records, quality certificates and other documents, and adapts to production intranet deployment scenarios |
REDIS_URL | redis://localhost:6379/0 | Caches real-time updated process parameters and batch status, reducing database query latency |
PG_URL | Points to the PostgreSQL database associated with the enterprise MES system | Synchronizes core business data such as batch numbers and process parameters |
FILE_TOKEN_KEY | Randomly generated 32-bit hexadecimal string | Generates file access tokens to ensure the security of document downloads |
ROOT_KEY | Strong password string compliant with enterprise permission specifications | Configures the system's highest privilege access key, ensuring operational security of production data |
Three Common Mistakes
- Symptom: After upgrading FastGPT v4.17.0, traceability rule display symbols appear at the end of quality audit conversations. Cause: The context traceability prompt switch added in the version update is enabled by default, and the corresponding configuration was not disabled during deployment.
- Symptom: After uploading video inspection data from the rolling process, the model cannot recognize the content. Cause: The FastGPT version that supports multimodality was not confirmed, and relevant storage and parsing parameters for multimodality were not configured.
- Symptom: Connection failure occurs after deploying MinIO, with an inaccessible prompt. Cause: MinIO was incorrectly configured to require public network access, which does not adapt to the enterprise intranet deployment scenario. The
STORAGE_S3_ENDPOINTwas not correctly set to point to the intranet node.
How to Verify Proper Configuration
- Run a bulk write test for single-batch steel coil data, and confirm that the database connection count does not exceed the configured
DB_MAX_LINKvalue. - Upload a rolling plan document, and verify that the parsed batch numbers match those in the enterprise MES system.
- Access the internal audit system domain name, and confirm that stored quality certificates and surface inspection reports load normally.
- Attempt to generate a quality audit conversation, and confirm that no traceability rule display symbols appear at the end.
The values provided are common starting points, and should be evaluated against the reader's own samples.