What data for this category looks like
The daily documents for this category include injection molding process cards, raw material drying records, mold histories, first-piece inspection forms, patrol inspection forms, and material change and machine cleaning records. Data sources cover resin batch property sheets, injection molding machine operating parameters, mold temperature controller data, MES system records, and dimensional and appearance inspection results. Data is updated after each production batch, each mold and material change, and each shift’s patrol inspection. Document fields include professional parameters such as filling pressure (unit: MPa), holding time (unit: seconds), drying temperature (unit: ℃), batch number, mold number, and more. Most documents follow a semi-structured industrial record format.
What constraints these characteristics impose on the vector models and indexing link
This category has high-frequency updated data, fields with specialized industrial parameters, and most documents are semi-structured production records. These traits create multiple constraints for the vector models and indexing workflow. Frequently updated production data requires indexes to support incremental updates, to avoid resource consumption from full reindexing. The semantics of specialized parameters must be adapted to industrial scenarios; embedding models must accurately identify the relationships between pressure, temperature, and fault descriptions. Long-text process cards and exception reports require reasonable chunking rules, to avoid breaking semantic connections between key processes and parameters, while controlling the token count of individual chunks to stay within model limits.
How to set configurations
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Ensures semantic integrity of individual sections of injection molding process cards and exception reports, avoids splitting connected content of filling and holding pressure processes and fault descriptions |
| Overlap Length | 100–150 characters | Preserves parameter context between adjacent chunks, prevents process flows from being broken by chunking |
| Similarity Threshold | Calibrated via actual testing | Adapts to semantic similarity judgments for industrial parameters, avoids mismatching similar process parameters from different batches |
| Single Search Limit | Top 6 results | Covers the number of associated documents for a single production batch, prevents redundant data from interfering with exception analysis |
maxToken | 4096 token | Ensures semantic integrity of long-text process documents, avoids truncation of critical parameter content |
defaultToken | 256 token | Balances retrieval accuracy and performance for short-text patrol records and raw material drying records |
Three common mistakes to avoid
- Indexes remain in the "indexing" state for extended periods and fail to complete construction. This occurs when a large volume of unprocessed raw injection molding machine logs are imported, and chunking is not performed in advance according to rules, leading to chunking calculation timeouts.
- Abnormally high similarity values appear in search results. This happens when a reasonable similarity threshold is not set, and the embedding model is not adapted to industrial parameter semantics, leading to text with the same unit parameters being judged as completely similar.
- The system prompts that the m3e model has no available channels. This is caused by failing to add a deployment channel for the m3e model on the system configuration page, and failing to complete the service address configuration required by official documentation.
How to confirm configurations are properly set
- Upload a single complete injection molding process card, check whether the system index completion status updates within 5 minutes, to confirm that the incremental indexing function is active.
- Enter a query statement containing specific faults and parameters, check whether the search results include associated documents such as corresponding mold histories and patrol records, to confirm that semantic matching is accurate.
- View the system embedding model configuration page, confirm that the channel for the m3e model has been added and is in an available state, with no error prompts.
- Upload a single raw material drying record, check whether the chunked text retains complete batch numbers, drying temperatures and duration information, with no critical content truncated.
The values given are common starting points and should be measured against the reader's own samples.