What this category of data includes
This category of data covers multiple departments including mining, raw meal, calcination, grinding, quality control and energy management. Data sources include online composition analysis, DCS systems, laboratory analysis, kiln and grinding equipment, raw and fuel ledgers, and energy metering devices. Daily documents include raw meal batching plans, kiln operation records, laboratory reports, quality control notices, equipment inspection records, and energy consumption reports. Data update cycles are divided into real-time, shift-based, and daily. Fields include raw and fuel parameters, equipment operation indicators, test results, and energy consumption values. No non-essential business statistical percentage content is included.
Constraints on source citation and traceability
The multi-source, time-staged update characteristics of this category of data impose three core constraints on the source citation and traceability link. First, rapid retrieval of real-time DCS and online composition data is necessary to avoid context overflow that slows response speed. Second, documents with different update frequencies must pair with corresponding traceability rules to ensure consistent citation logic for shift-based inspection records and daily laboratory reports. Third, batching plan adjustments during raw and fuel fluctuations require accurate tracing of corresponding ledger data to avoid clinker quality fluctuations or rotary kiln scaling and shutdown caused by incorrect citations.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale | |
|---|---|---|---|
quoteMaxToken | 800–1200 token | Adapts to the mixed length of real-time DCS data and laboratory reports, avoiding context overflow | |
responseData | Only retrieve category-matching data | Filters irrelevant cross-scenario data, focusing on the business scope of cement clinker and grinding | |
detail | Top 3 traceability entries | Matches the core citation needs of production documents, avoiding information overload | |
| Retrieval trigger similarity | 0.70–0.80 | Calibrated through actual measurements | Adapts to the text matching accuracy of raw and fuel ledgers and kiln operation records |
Three Common Misconfigurations
- The response body excludes matching content from the local knowledge base, while the citation list displays correct cement production document entries. Incorrect configuration of the
responseDataparameter causes matching data to be excluded from the response body. - The number of returned traceability entries exceeds the preset range. An overly high setting for the
detailparameter causes more retrieved entries than the core citation needs of production documents allow. - Interface calls time out. An overly large
quoteMaxTokensetting increases context loading time beyond the response time limit of production scenarios.
How to Verify Successful Configuration
- Submit a query containing keywords from the raw meal batching plan, and check for matching laboratory report and DCS data citations in the response body.
- View the traceability display area, and confirm that only document entries related to cement clinker and grinding appear, with no cross-scenario data.
- Adjust configuration parameter values, and confirm that response length and number of retrieved entries change as expected with parameter adjustments.
- Call the API interface under FastGPT v4.17.0, and confirm that the returned
responseDatafield contains the configured matching data scope.
The values provided here are common starting points, and should be evaluated against the reader's own operational samples.