What the data for this category looks like
Data sources for the basic chemical continuous production category include DCS/SIS systems, online analyzers, LIMS laboratory management systems, equipment condition monitoring modules, energy metering devices, and raw material storage tank data terminals. Data update frequencies fall into three categories: real-time, shift-based, and daily, corresponding to process parameters, shift logs, and daily ledgers. Daily documents include operating procedures, process index cards, DCS trend charts, test reports, interlock bypass records, special work permits, and shift reports. Most fields use chemical-specific units, such as reaction temperature (℃), system pressure (MPa), material flow rate (m³/h), and raw material inventory (tons). This guide is compatible with FastGPT v4.17.0.
What constraints these characteristics impose on workflow orchestration
Data sources for this category are scattered, and their update rhythms vary significantly. This requires workflows to support differentiated pull configurations for multiple data sources, with distinct node trigger logic for real-time parameter synchronization and batch ledger summarization. The wide variety of daily document types means workflows must adapt parsing components for structured process data, semi-structured test reports, and unstructured shift report text, to prevent format parsing failures. Chemical-specific fields use fixed units, so workflows must include unit validation nodes to avoid calculation errors caused by mismatched parameter units. Additionally, since errors can lead to severe consequences, workflows must configure failure retry mechanisms and exception alert trigger nodes to ensure process stability.
How to Set Configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Data Source Trigger Rules | Configure by update frequency groups | Match the different update rhythms of DCS real-time data, shift reports, and daily ledgers |
| Parsing Mode Selection | Structured + text chunking dual mode | Adapt to parsing requirements for DCS tabular data and shift report text |
variables Configuration | Bind chemical field and unit mappings | Ensure units match fields during parameter transfer |
| Node Timeout Setting | 600 seconds | Cover calculation and validation durations for complex process data |
nodeId Association Rules | Bind by process node sequence | Ensure correct execution order logic for workflow nodes |
| Failure Retry Configuration | Up to 3 retries, 30-second interval | Address temporary data source fluctuations or parsing anomalies |
Three Common Misconfigurations
- Symptom: Input is empty when advancing a global variable debug to the next node. Cause: The scope of the
variablesparameter was not correctly bound in the workflow, so session-level variables are not passed to subsequent nodes. - Symptom: Files uploaded via simple tasks cannot have their links passed as parameters to the workflow. Cause: The output of the file parsing node was not configured to associate with the workflow's input parameters, so the file link is not correctly extracted.
- Symptom: A node timeout error occurs during workflow execution. Cause: The node timeout setting duration does not match the calculation cycle of the process data, so the timeout trigger activates before the process completes.
How to Verify a Correct Configuration
- Trigger the data source matching the target update rhythm, and verify that the workflow starts execution per the preset rules.
- Upload a typical document from the category, and confirm that the parsing results match the preset field and unit mappings.
- Simulate a node execution exception, and confirm that the failure retry and alert logic activate as configured.
- Call the workflow as a tool, and check that incoming parameters are fully passed to the target nodes.
The configuration values provided are common starting points, and should be evaluated against your own specific samples and operational requirements.