What this category’s data looks like
Production data for iron and steel smelting and continuous casting comes from:
- Hot metal and scrap charging records
- L2 process control systems
- Laboratory composition reports
- MES production management systems
- Energy medium monitoring systems
- Equipment status monitoring modules
Daily production documents include heat plans, batching lists, converter smelting records, continuous casting process parameter records, and slab quality judgment sheets. Each document includes fields such as heat number, cast number, real-time temperature, composition content, and operation time. Update frequencies span per-heat, real-time, and shift cycles. Smelting and continuous casting data for a single heat has a strong coupling relationship.
Constraints on citation source and traceability processes
Because data updates per heat and in real time, and has strong coupling, the traceability process must accurately associate with specific production batches to avoid mixing data across heats. Documents from multiple systems have different formats. The traceability process must match the original data collection module and timestamp. High-temperature continuous production processes cannot tolerate excessive response delays. Traceability configuration must not consume too many real-time computing resources. At the same time, incorrect citations in process Q&A directly lead to heat downgrading or scrapping. The accuracy of traceability directly affects the reliability of production decisions.
How to configure settings
The following configurations are compatible with FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the typical length of a single heat’s process record, prevents mixing data across heats during chunking |
| Overlap Length | 150 characters | Retains key identifiers such as heat number and cast number, prevents loss of cross-process association information after chunking |
quoteMaxToken | 6000–10000 tokens | Adapts to the total token count of multiple smelting and continuous casting records, ensures Q&A context covers complete process logic |
responseData | Includes source document path, heat number, collection time | Meets core requirements for tracing back to specific production batches and data sources |
detail | Enabled | Displays complete process fields such as composition and temperature, allows production personnel to verify the accuracy of cited content |
| Single Recall Limit | Top 5 entries | Controls context scale, avoids redundant data interfering with real-time Q&A response speed |
Three common misconfigurations
- Issue: After 100 process documents are batch uploaded, knowledge base recalled citations mix data across heats. Cause: Chunk length is set too small, causing a single chunk to contain process data from multiple heats, making accurate matching to a single heat impossible during traceability.
- Issue: The setting entry for large model temperature cannot be found in variable reference mode. Cause: The advanced configuration panel for variable references is not correctly bound in the conversation component, or the display switch for the corresponding parameter is not enabled.
- Issue: Empty ID is displayed during citation traceability, or original documents cannot be associated. Cause:
responseDatais not configured to return the unique identifier field of the source document, so the system cannot match the original production data in the knowledge base.
How to confirm correct configuration
- A single complete heat process record is uploaded. A Q&A for the corresponding process question is initiated. Check if the citation source labels the heat number and collection time.
- Multiple production documents of the same type are batch uploaded. A cross-heat comparison Q&A is initiated. Verify that recalled citation content is categorized by heat, with no cross-batch mixing.
- In variable reference mode, a conversation is tested and temperature parameters are adjusted. Verify that Q&A results adjust accordingly as parameters change.
- An abnormal upload scenario is triggered. The knowledge base’s exception logs are reviewed. Confirm that re-uploaded documents are automatically deduplicated, with no duplicate citation records.
The values provided are common starting points and should be validated against in-house samples.