What this category of data looks like
This category of data covers content related to the full lifecycle of manufacturing enterprise equipment. Sources include EAM/CMMS systems, equipment sensor collection data, operator point inspection records, maintenance work orders, spare parts inventory ledgers, and statutory inspection documents for special equipment. Update cadences include shift-based point inspection submissions, weekly maintenance plan updates, monthly spare parts inventory counts, and immediate record supplements when faults occur. Daily documents include equipment ledgers, point inspection forms, maintenance work orders, fault analysis reports, and more. Fields include equipment number, point inspection items, spare part model, inspection validity period, and others. No additional statistical figures or percentages are included.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Data sources for this category are scattered. They include structured equipment ledgers and spare parts lists, plus unstructured fault analysis reports and point inspection records. The retrieval system must support both structured field matching and full-text search. The frequent update cadence requires the recall link to support incremental synchronization and scheduled full updates. This avoids data lag that could affect maintenance decisions. Emergency query needs during fault occurrences require the retrieval link to have low latency. The system must also match common terminology used by maintenance teams, such as "point inspection abnormality" and "spare part replacement". This improves recall accuracy. The statutory nature of special equipment inspection records requires recall results to be associated with accurate inspection validity period fields. This prevents missing compliance-related information.
How to Configure Settings
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.80 | This category has highly specialized equipment terminology. A threshold in this range filters low-relevance results, preventing maintenance teams from being distracted by unrelated point inspection records |
limit | Top 8 entries | Maintenance teams need to quickly access core reference materials. Too many results increase information filtering costs |
usingReRank | Enabled | Multiple synonyms exist for equipment fault descriptions. Reranking optimizes result sorting and improves fault localization efficiency |
datasetSearchUsingExtensionQuery | Enabled | Abbreviations are common in point inspection and maintenance terminology. This optimization covers more potential matching scenarios |
searchMode | mixedRecall | Data includes both structured fields and unstructured text. Hybrid retrieval balances precise matching and full-text recall |
collectionIds | Actual bound IDs of equipment-related knowledge base collections | The retrieval scope must be limited to documents related to equipment point inspection and maintenance, to avoid mixing in data from other categories |
Three Common Configuration Errors
- Phenomenon: Some PDF documents cannot be recognized, and the interface displays parsing failure. Cause: The documents contain encrypted content or non-standard printed fonts. Equipment point inspection forms often have nested tables and handwritten annotations, which exceed the scope of basic parsing adaptation.
- Phenomenon: Retrieval results are returned all at once, without streaming interactive experience. Cause: FastGPT streaming response configuration is not enabled, and streaming push logic is not adapted for Feishu bots.
- Phenomenon: A prompt indicates no matching content during retrieval. Cause: The configured
collectionIdsonly bind non-equipment-related knowledge bases, or thesimilaritythreshold is set too high, filtering all valid recall results.
How to Verify the Configuration is Correct
- Upload one equipment point inspection form PDF. Confirm the parsed text includes core fields such as point inspection items and equipment number, with no missing content or garbled text.
- Initiate a fault query, such as "Key inspection points for pump body abnormal noise". Confirm the returned results are sorted according to business priority and include relevant documents such as work orders and fault analysis reports.
- View the knowledge base synchronization log. Confirm that shift-based and daily equipment data update tasks run normally, with no failed records.
- Test adjusting the
similarityparameter. Observe changes in the number of recall results, and confirm the threshold configuration takes effect.
The values provided here are common starting points, and should be evaluated against samples from the actual deployment.