What this category of data looks like
This category of data includes slab or billet batch ledgers, furnace operating parameters, mill automatic control logs, online thickness and width measuring equipment data, surface inspection results, and manufacturing execution system (MES) data. Daily documents include rolling plans, heating schedules, rolling specifications, flatness and thickness records, surface quality reports, and product quality certificates. Data updates in real time per coil or per billet, supporting full-link traceability at the coil level. Document fields include process parameters, measured values, batch identifiers, and more, using industrial standard units such as millimeters, degrees Celsius, and meters per second.
What constraints these characteristics impose on workflow orchestration
The real-time coil-level data and multi-source document characteristics of this category impose three core constraints on workflow orchestration. First, the real-time data update rhythm requires workflow triggering timing to match the production node of a single coil or billet. Fixed-period scheduling is not used. Second, the coil-level traceability requirement requires the workflow to dynamically bind the batch ID as the variables parameter, ensuring retrieved and processed documents fully correspond to the target production batch. Third, the multi-source and heterogeneous process and inspection document types require the workflow to configure multiple parallel retrieval nodes for different document types, then aggregate results for output. Additionally, abnormal process parameters may cause coil downgrading or equipment damage. The workflow must embed an anomaly judgment node that matches industry conventional parameter thresholds.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Global variable variables | Bind rolling batch ID and coil specification parameters | Match coil-level traceability requirements, ensure retrieved and processed documents correspond to the target production batch |
Node ID nodeId | Assign unique identifiers to heating schedule, rolling specification, and inspection report nodes | Distinguish multi-source retrieval nodes to avoid confusion during data aggregation |
| Single retrieval context length | 800–1200 characters | Adapt to the single-paragraph information volume of industrial process documents |
| Single retrieval upper limit | Top 5 entries | Control the number of returned results to avoid redundant data interfering with judgment |
| Timeout threshold | 600 seconds | Match conventional industrial production response time requirements |
| Log retention period | 30 days | Comply with industrial production compliance traceability requirements |
This configuration example is based on FastGPT v4.17.0.
Three Common Misconfigurations
- Issue: A 400 error is returned when an HTTP request node transmits TXT format process documents. Cause: The
variablesparameter is not correctly configured to bind the file stream. Only the file name is transmitted, not the actual file content. - Issue: The workflow cannot retrieve process specifications corresponding to the target coil. Cause: The batch ID is not dynamically passed to the retrieval node as the
variablesparameter, leading to retrieval results matching incorrect batch data. - Issue: Multiple workflows cannot be mounted in the Bot. Only a single workflow can run independently. Cause: The multi-workflow mounting function is not enabled in the Bot configuration. The workflow is incorrectly bound as a single functional module.
How to Confirm Proper Configuration
- Trigger a simulated batch creation event, check whether the workflow starts automatically and retrieves process documents for the corresponding batch.
- Check whether the
variablesparameter is correctly bound to the current batch’s ID and specification parameters, with no null values or incorrect fields. - Verify that the HTTP request node can normally transmit TXT format documents to the backend, and returned results meet expectations.
- Confirm that the workflow has been mounted in the Bot configuration, and the workflow can be triggered and executed via conversation to return results.
The values provided are common starting points and should be measured against the reader's own samples.