What the data for this category looks like
Data sources for continuous basic chemical production include DCS/SIS systems, online analyzers, LIMS systems, equipment condition monitoring, energy metering devices, and raw material tank data nodes. Daily documents cover operating procedures, process index cards, DCS trend charts, laboratory reports, interlock bypass records, special work permits, and shift logs.
Data update frequencies fall into three categories: real-time, per-shift, and daily. Process index cards and interlock bypass records are mostly updated per shift. DCS trends and online analyzer data are updated in real time. Laboratory reports and shift logs are updated daily.
Document fields include process pressure (unit: MPa), reaction temperature (unit: ℃), tank liquid level (unit: m), interlock trigger thresholds, work permit numbers, and others. These fields comply with industry standard units.
Constraints imposed on workflow orchestration
Multiple data sources and differentiated update frequencies require workflows to support execution based on each node’s trigger rhythm. Real-time data nodes require configured appropriate trigger intervals. Shift log nodes require configured daily scheduled triggers.
Differences in fields and units across document types require workflows to add verification logic during variable processing. This prevents cross-unit parameter comparison errors.
Different documents belong to distinct business categories. Workflows must call knowledge bases in groups according to business scenarios to avoid mixing content categories such as compliance verification and expert interpretations.
The timeliness of real-time data requires workflow node execution durations to match the data update window. This prevents data lag caused by timeouts.
Configuration Recommendations
Based on FastGPT v4.17.0 workflow orchestration, the following configuration suggestions apply:
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Custom input variables | Bind variables to the process pressure, reaction temperature, and tank liquid level fields | Match the core process data fields of continuous basic chemical production |
| Node ID trigger | Bind DCS real-time data nodes and shift log update nodes by nodeId | Adapt to the two update rhythms of real-time and per-shift |
| Knowledge base grouped calls | Call in 3 groups according to business regulations, expert interpretations, and compliance verification | Correspond to the classification of different types of technical documents |
| Single search limit | Top 8 entries | Cover the recall volume of multiple types of documents such as process indicators and interlock records |
| Unrelated question fallback | Configure fixed reply text | Handle questions unrelated to compliance verification |
| Timeout setting | 600 seconds | Match the time consumption requirements of pulling multiple data sources and querying multiple knowledge bases |
Three Common Misconfigurations
- The workflow runs with a timeout and returns a 504 status code. This occurs when the timeout threshold is not adjusted for multi-data source pulling in continuous basic chemical production, as the default timeout duration is insufficient.
- A question unrelated to the preset knowledge base triggers the knowledge base AI answer branch. This occurs when no unrelated question fallback node is configured, so the workflow does not split traffic per preset rules.
- The HTTP custom input node returns empty fields. This occurs when
variablesare not bound to the request parameter format of the corresponding interface, and the field naming rules of basic chemical documents are not matched.
How to Verify Successful Configuration
- Trigger a DCS real-time data update, and confirm the workflow executes the corresponding nodes per the configured trigger rules.
- Input a question unrelated to compliance verification, and confirm the preset fallback reply text is returned.
- Confirm the process parameters bound to
variablesare correctly passed to the HTTP custom input node. - Test the three knowledge base grouped calls, and confirm each group returns corresponding types of document content.
The values provided here are common starting points, and should be evaluated against the reader's own samples.