What this category of data looks like
This category of data comes from slab or billet batches, heating furnaces, mill automation controls, online thickness and width measurement, surface inspection, and MES systems. Daily generated documents include rolling plans, heating schedules, rolling specifications, shape and thickness records, surface quality reports, and quality certificates. Data is updated per coil or billet, with real-time update cycles. Document fields include batch number, heating temperature, mill reduction amount, thickness deviation value, surface defect type, and more. Units include degrees Celsius, millimeters, meters per second, percentage, and others.
What constraints these characteristics impose on the "workflow orchestration" link
Real-time, coil- or billet-specific data updates require workflow triggers to be tied to billet processing progress, to avoid calling outdated data. The multi-type, multi-field document structure requires workflows to split execution nodes by document category, to match different field validation rules separately. Dispersed data sources require workflows to integrate variables parameters from multiple systems, to ensure each step uses the exclusive data for the current batch. Severe error consequences require workflows to set exception branches, to trigger alerts or terminate processes when shape deviations or temperature anomalies are detected.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Maximum Search Limit | Top 8 entries | Covers associated fields of the four core document types involved in a single batch's rolling: rolling plans, heating schedules, shape and thickness records, and surface quality reports |
| Question Optimization | Before node execution | Corrects professional terminology errors in industrial documents in advance, to ensure the accuracy of model comparisons |
| Maximum Context Window | 12000 token | Accommodates complete field information for multiple documents in a single batch, to avoid truncation of critical batch-associated data |
variables | Bind current batch MES and online inspection data | Ensure the workflow calls real-time exclusive parameters for the current processing coil |
| Timeout Threshold | 300 seconds | Matches the average time required for industrial data retrieval and document comparison, to avoid long-term process blocking |
Three Common Misconfigurations
- Workflow dialogs show failure, but the model backend has response logs. This occurs because
variablesbound to the current batch's exclusive data are not configured, leading to missing core parameters such as batch number and thickness value when the model is called, making document cross-comparison impossible. - Intelligent agent node triggers an error. This occurs because the timeout threshold is not set, or is set too short, causing industrial data retrieval and document comparison to exceed the set time, triggering node failure.
- Question optimization component is placed incorrectly. This occurs because the component is placed after the document recall node, causing already recalled documents to not have their professional terms corrected, leading to deviations in comparison results.
How to Confirm Proper Configuration
- Manually trigger a single batch test, enter the rolling plan number of a known batch, and verify whether the
variablescalled by the workflow include the heating temperature and mill reduction data corresponding to that batch. - Simulate a data delay scenario, and verify whether the exception handling branch is triggered after the timeout threshold is exceeded.
- Check that the question optimization component is located before all document recall nodes, to ensure professional term correction takes effect.
- View the FastGPT v4.17.0 workflow logs, and confirm that the execution order of each
nodeId-corresponding step matches the configuration.
The values provided here are common starting points, and should be evaluated against the reader's own samples.