What the data for this category looks like
Core data for stamping and sheet forming workshops comes from steel coil labels and quality certificates, press and feeder operation logs, mold management systems, MES systems, and coordinate measuring machine dimensional inspection data. Daily documents include stamping work instructions, material utilization rate sheets, mold inspection sheets, first/last piece records, dimensional inspection reports, and mold change records. Data update frequency is triggered per steel coil, per production batch, and per mold change. Single document fields include steel coil number, mold model, blank holder force parameters, mold change time, material thickness, inspection deviation value, and more, with units including millimeters, hours, tons, kilonewtons, and others.
What constraints these characteristics impose on the vector models and indexes link
This category’s data has high update frequency and strong interconnections. New ledger records are generated for each steel coil and each mold change, requiring vector indexes to support incremental updates instead of full reindexing to avoid excessive computational resource usage. Single documents contain multi-dimensional associated fields, such as mold number bound to mold change records, and material batch associated with utilization rate data. The index must retain field-level metadata to support precise retrieval. Additionally, workshop production processes such as layout planning and drawbead debugging rely on historical ledger data. The recall speed and accuracy of the index directly affect production efficiency, so it must match the response requirements of production links.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the average length of single stamping ledger records, avoids splitting key associated fields such as mold number and mold change time |
| Overlap Length | 50–80 characters | Retains associated information such as molds and material batches across chunks, prevents chunking from breaking data context |
| maxToken | Set to the selected embedding model/service maximum supported input tokens | maxToken is the input-token maximum supported by the selected embedding model/service; verify it in that provider configuration. See the v4.17.2 model-field reference. It is not retrieval/LLM context or a FastGPT-wide fixed cap. |
| Similarity Threshold | 0.75–0.85 | Differentiates ledger records for different molds and material batches, reduces false recall probability |
| Single Search Limit | Top 10 entries | Matches the common result volume for daily workshop retrieval, avoids returning excessive redundant data |
| defaultToken | 1000 | Sets the maximum token count for single vectorized text, adapts to the short-text characteristics of stamping ledgers |
Three Common Misconfigurations
- Phenomenon: When repeatedly initiating the same production ledger summarization query, the system response delay exceeds expectations. Cause: No vector retrieval caching mechanism is configured. Each request re-traverses the index and calculates similarity, without reusing historical retrieval results.
- Phenomenon: After calling the knowledge base interface to create a training order, adding mold change records to the collection fails. Cause: The trigger logic for training orders and incremental indexes is confused. Corresponding data files are not associated by production batch, resulting in missing index metadata.
- Phenomenon: Image attachments of dimensional inspection reports are not included in retrieval results. Cause: Image vectorization configuration is not enabled, or image metadata is not bound to text indexes, making joint text-image retrieval impossible.
How to Verify Successful Configuration
- View the metadata tag list of the vector index, confirm inclusion of stamping workshop-specific fields such as steel coil number, mold model, and mold change time.
- Batch import mold change records and material utilization rate sheets for a single production batch, check for completion of index update status within the set incremental update cycle.
- Initiate a retrieval request containing a specific mold number, check that the number and relevance of returned results meet the set similarity threshold.
- Initiate the same ledger summarization query twice, confirm a significantly lower response delay for the second query, verifying activation of the caching configuration.
The values provided are common starting points and should be measured against relevant operational samples.