What This Category of Data Looks Like
Core data for forging and die forging scenarios comes from raw material quality certificates, furnace heating system data, press collection data, MES systems, non-destructive testing equipment, and customer forging drawings. Daily operation and production documents include forging process specifications, cutting lists, furnace heating records, forging process cards, mold life records, heat treatment work orders, and ultrasonic testing reports. Data updates are performed per individual forging, batch of materials, or furnace heat. Fields include forging ratio, fiber direction, furnace batch number, mold number, testing values, and more. Units include physical quantities such as millimeters, degrees Celsius, tons, and others.
Constraints Imposed by These Characteristics on the Citation Source and Traceability Link
Since data is updated per individual unit, batch, or furnace heat, traceability must accurately bind to the corresponding production node of the batch to avoid cross-batch citation confusion. Structural differences across multiple document types require the traceability system to recognize the field specifications of different documents. For example, the furnace batch number on a cutting list must correspond to the testing number on an ultrasonic testing report. The collection link across multiple data sources requires that traceability information can be traced back to the original system, and cannot rely solely on secondarily processed documents. Additionally, the consequences of forging part failure are severe, so traceability must ensure that cited content fully corresponds to the actual parameters of the production link, with no information truncation or fuzzy matching.
How to Configure
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
| Similarity Threshold | 0.75–0.85 | Forging process parameters have high precision requirements, requiring filtering of irrelevant documents with low matching degrees |
| Single Recall Limit | Top 8 entries | The number of forging-related documents is concentrated, and excessive recall will exceed the context carrying limit |
quoteMaxToken | 1200–1500 token | Forging process specification texts are long, requiring retention of complete citation fragments |
responseData | Enable original citation fields | Directly return the original reply of the knowledge base Q&A pair, without AI rewriting |
detail | Enable traceability details | Display the source node and batch information of the cited document |
| Chunk Overlap Length | 50–80 characters | Cover continuous step descriptions in the process specification, avoiding truncation of key parameters by chunking |
Three Common Mistakes
- Phenomenon: The AI return result in the workflow does not carry the queried knowledge base content, only returns a general prompt. Cause: The
responseDataconfiguration item is not enabled, so the system does not retain the reply content of the original Q&A pair. - Phenomenon: The service has no response for a long time after startup, and the request triggers a timeout. Cause: The single recall limit is set too high, and the value of
quoteMaxTokenis too large, exceeding the system context carrying limit. - Phenomenon: Cited content is truncated, and complete heating interval or deformation step parameters cannot be viewed. Cause: The value of
quoteMaxTokenis too small, failing to cover the complete process specification fragment.
How to Confirm the Configuration Is Properly Set
- Initiate a query that includes a specific forging part furnace batch number, and check whether the returned result includes the original reply of the corresponding knowledge base Q&A pair.
- View the traceability details field in the returned result, and confirm whether it is associated with specified production data sources such as raw material quality certificates and furnace heating records.
- Test queries for different batches of forgings, and verify that the recall results only match the process documents of the corresponding batch, with no cross-batch confusion.
- Adjust the value of
quoteMaxToken, and check whether the integrity of the citation fragment meets the reading requirements of production documents.
The values provided are common starting points and should be measured against the reader's own samples.