What This Category of Data Looks Like
Business process data for iron and steel smelting mainly comes from manufacturing execution systems (MES), furnace condition monitoring systems, and quality inspection laboratory systems. Data is archived by heat. Each document includes fields such as heat number, steel grade, smelting start time, target temperature range, real-time furnace temperature, argon blowing flow rate, tapped metal weight, and final carbon content. Their units are, respectively: string, steel grade, ISO timestamp format, degrees Celsius, degrees Celsius, cubic meters per hour, tons, and milligrams per kilogram. Real-time furnace temperature data updates every 10 seconds. Full heat data is synchronized within 1 minute after smelting ends. Quality inspection data is updated within 4 hours after sampling.
Constraints on Workflow Orchestration From These Characteristics
The real-time nature and strong correlation of iron and steel smelting business data create multiple constraints for workflow orchestration. High-frequency updates of real-time furnace temperature require the workflow to use a reasonable variable pull interval, to avoid data lag affecting process judgment. Strong correlations between fields (such as the direct link between argon blowing flow rate and final carbon content) require workflow nodes to set dependencies based on business logic. This ensures downstream nodes only trigger when upstream data is complete. Delayed quality inspection data updates require the workflow to include wait nodes and exception branches, to handle quality inspection results that are not synchronized on time. The multi-level business approval process structure requires the workflow to support branching node triggers, to adapt to handling paths for different exception scenarios.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind heat number, real-time furnace temperature, and argon blowing flow rate variables; set update interval to 10 seconds | Steel smelting real-time data updates every 10 seconds, so latest collected values must be synced to the workflow |
| Node trigger conditions | Trigger based on upstream node output results bound by nodeId | Ensure the workflow executes in business logic order, preventing unbound nodes from running prematurely |
| Timeout processing duration | 4 hours | Match the maximum update delay of quality inspection data, ensuring subsequent approval steps run only after data is complete |
| Form field configuration | Set heat number, exception type, and processor fields; enable required validation | Clearly associate with the corresponding heat, and standardize record information for exception handling |
| Context transfer limit | Top 8 historical interaction records | Adapt to multi-level interaction scenarios in iron and steel smelting business, retaining context information from key nodes |
| Exception branch rule | Trigger parameter adjustment branch when real-time furnace temperature exceeds target range | Match furnace condition exception handling logic, enabling dynamic branching of the workflow |
Three Common Mistakes
- Phenomenon: After the workflow is published to an external interface, the call returns a "missing parameter" error. The log shows global variables were not included in the interface input parameters. Cause: Required global variables were not bound in the
variablesconfiguration, or the mapping relationship between interface input parameters and variables was not specified. - Phenomenon: When the workflow runs a multi-level branch process, some branches do not trigger the inquiry node. The number of returned interaction results does not match the preset business path. Cause: The trigger dependency for
nodeIdwas not configured correctly, causing the branch node to not bind conditional parameters from upstream output. - Phenomenon: After custom variables are spliced, they do not match business document content. The system prompts that the variable cannot be added. Cause: Variables were not configured according to the field format of iron and steel smelting business data, or variable naming did not match the system recognition rules.
How to Confirm the Configuration Is Complete
- Enter the workflow
variablesconfiguration page in FastGPT v4.17.0, and verify that bound variables include business-required fields such as heat number and real-time furnace temperature. - Initiate a simulated call, pass parameters for a test heat, and check whether the workflow triggers the corresponding nodes and transfers variables correctly as configured.
- Simulate an exception scenario where real-time furnace temperature exceeds the target range, and check whether the corresponding inquiry node pops up and the correct branch workflow is generated.
- Wait 4 hours, and check whether the workflow automatically triggers the node waiting for quality inspection data and completes the subsequent process.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.