What data looks like for this category
This category of data is sourced from ERP material master data, melting furnaces and thermometers, spectrometers, MES heat records, mold management systems, and customer drawing technical specifications. Daily documents include casting process cards, batching lists, heat records, mold histories, first-piece inspection records, material reports, and nonconforming product review forms. Fields cover alloy composition ratios, melting temperatures, mold cycles, nonconforming defect types, and more. Units include degrees Celsius, percentage, kilograms, and others. Data update frequency is per heat, per batch, or daily, with real-time or periodic updates aligned with production rhythms.
What constraints these characteristics impose on deployment and upgrade
Multi-source industrial system data sources require deployment to support connecting to devices and business systems using different protocols, and adapt to access permission restrictions in the workshop intranet. High-frequency real-time updates require deployment nodes to have stable concurrent processing capabilities to avoid data synchronization delays. Industry-specific document fields and units require configuring field mapping rules during deployment, to ensure the Q&A system can accurately recognize professional terminology and data formats in foundry scenarios. Accumulated heat and mold data will continuously occupy storage resources, so capacity configuration for databases and object storage must be planned in advance.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 10–20 connections | Adapts to high-frequency heat data queries and synchronization requests in foundry scenarios, avoiding database connection exhaustion |
MONGODB_URI | Points to the intranet cluster address storing heat records and mold histories | Used to persistently save Q&A logs for equipment inspection and maintenance, as well as vector data of foundry industry documents |
REDIS_URL | Configured as the workshop local cache node address | Caches frequently queried melting temperature and alloy batching ratio data, reducing call pressure on external systems |
FE_DOMAIN | Fill in the workshop intranet frontend access domain name | Used to embed into existing production system frontend pages to enable embedded calls of the equipment inspection process |
STORAGE_S3_ENDPOINT | Points to the workshop intranet object storage service address | Stores attachment data such as material reports exported by spectrometers and nonconforming product review forms |
ROOT_KEY | Access key calibrated through actual testing | Used to manage the highest permissions of deployment instances, adapting to local deployment permission control in foundry workshops |
Three common errors
- Phenomenon: After deployment, access is only possible via API, and no embeddable frontend page can be found. Cause: After upgrading to FastGPT v4.17.0, the release configuration for the frontend embedding module is disabled by default. The frontend deployment parameter must be manually enabled.
- Phenomenon: A database connection failure error pops up during Docker Compose local deployment. Cause: The data source address pointed to by
MONGODB_URIorPG_URLis not correctly configured, or the database access port of the workshop intranet is not open. - Phenomenon: After executing the conversation record cleanup operation, historical sessions can still be queried. Cause: The cleanup command was not executed with
ROOT_KEYpermissions, or the Redis cache instance was not stopped, resulting in residual session data not being fully cleared.
How to confirm the configuration is correct
- Access the intranet domain name configured in
FE_DOMAIN, confirm that the frontend page for equipment inspection and maintenance Q&A loads normally, and that inspection questions can be submitted and replies obtained normally. - Execute a database connection test command, confirm that the current number of connections is within the range set by
DB_MAX_LINK, with no connection exhaustion or timeout issues. - Upload a casting process card PDF file or a casting defect image, confirm that the file can be stored via
STORAGE_S3_ENDPOINTand its content can be read normally. - Execute the conversation record cleanup command using
ROOT_KEY, confirm that the corresponding session data has been cleared with no residual content left.
The values provided are common starting points and should be measured against the reader's own samples.