What the Data for This Category Looks Like
Data for steel rolling and finishing operations is sourced from slab or billet batches, heating furnaces, mill automatic control systems, online thickness and width measurement equipment, surface inspection devices, and MES systems. Data updates in real time per coil or individual steel material. Daily generated documents include rolling plans, heating schedules, rolling specifications, flatness and thickness records, surface quality reports, and quality certificates. Document fields include batch number, heating temperature (unit: ℃), rolling reduction, thickness (unit: mm), width (unit: mm), surface defect type, hardness value, and more. Field association across different documents relies on steel batch identifiers.
Constraints Imposed on Workflow Orchestration by These Characteristics
Real-time, batch-based data requires workflows to support triggering execution per steel batch, to avoid delays caused by fixed-cycle polling. Multi-source data input requires workflows to integrate collected data from different nodes, ensuring field matching between rolling specifications, online inspection results, and MES records. The volume of documents per coil or individual steel material is moderate but closely linked. Workflows must retain complete field associations and must not arbitrarily split data. Exception determination must directly link to real-time inspection data. If a workflow step fails, it can directly lead to steel coil downgrading, equipment damage, and other consequences. Therefore, clear exception branches and retry mechanisms must be configured.
How to Set Configurations
These configurations are based on FastGPT v4.17.0 logic.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Variable update trigger mode | Triggered on variables change | Adapt to real-time batch data updates, avoid delays from fixed polling, and ensure process document updates sync with steel material progress |
| Single-node context length | 800–1200 characters | Match the typical character volume of single-coil rolling records, avoid processing failures caused by exceeding AI context limits |
| Exception retry count | 3 times | Balance exception handling efficiency and loss risk for equipment and batches, avoid excessive retries occupying production resources |
| Exception branch trigger condition | Use nodeId execution failure status code | Accurately locate exceptions in specific links such as rolling and inspection, and trigger the corresponding exception report drafting process |
| Batch data association rule | Match by steel material batch number | Ensure inspection and plan data from different sources are linked to the corresponding steel coil, avoid data misalignment |
Three Common Misconfigurations
- Symptom: Global
variablesvalues do not update automatically. Cause: The workflow node is not configured to trigger on variable changes, and only a fixed polling execution cycle is set. - Symptom: Workflow execution times out. Cause: The processing length of single-batch data is not limited, and the imported complete rolling record exceeds the AI context limit.
- Symptom: Exception report classification is incorrect. Cause: Real-time data from the mill automatic control system is not used as the classification basis, only static historical document templates are used.
How to Verify Correct Configuration
- Trigger a variable update for a single steel coil, check if the
variablesfield synchronously updates to the latest data for the current batch. - Simulate a failed execution of an exception node, confirm whether the workflow automatically jumps to the exception branch and triggers the exception report drafting process.
- Import a complete set of rolling record documents for a single batch, check if the workflow fully loads all fields and completes association matching.
- View the workflow execution log, confirm that the trigger conditions match the configured
variableschanges andnodeIdstatus.
The values provided are common starting points and should be measured against the reader's own samples.