What this category's data looks like
Pulp and papermaking process and exception data comes from wood pulp and waste paper batch ledgers, DCS/QCS control systems, on-paper machine measurement equipment, laboratory testing systems, and energy and water treatment systems. Data update frequencies include real-time (such as paper machine operating parameters), shift-based (such as team production records), and per-roll (such as finished paper batch records). Typical documents include pulp preparation sheets, beating operation records, paper machine operation logs, online quality curves, laboratory test reports, and sheet break and product change ledgers. Fields include pulp ratio values, beating degree °SR, paper basis weight g/㎡, operating temperature ℃, sheet break duration minutes, and other relevant metrics.
What constraints these characteristics impose on workflow orchestration
Data sources for this category are scattered, and format differences are significant. Field names and units from different systems are inconsistent. This requires configuring multi-source data pulling and format alignment nodes during workflow orchestration. Data update frequencies cover real-time, shift-based, and per-roll. Corresponding workflows must distinguish trigger rules. Real-time parameters need high-frequency trigger nodes. Batch records need scheduled trigger nodes. High-speed continuous web production characteristics require that exception workflows start quickly after sheet break or product change events. Delayed report generation that affects production adjustments must be avoided.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Trigger Mode | Trigger based on event types defined in variables. Use second-level polling for real-time parameters, scheduled per shift or per roll for batch records | Match the multiple update rhythms of pulp and papermaking data. variables can flexibly bind trigger conditions for different data sources |
| Data Source Node | Pull ledger and real-time data from corresponding systems, associate permission configurations bound to nodeId | Ensure the workflow only calls production data within authorized scope. nodeId can accurately locate individual data source nodes |
| Context Length | 800–1200 characters | Adapt to the text length of single-roll paper machine operation records, avoid context overflow that affects generation quality |
| Output Aggregation Rule | Only retain the generation result of the final node, hide the output of preceding AI calls | Meet the output requirements of process documents and exception reports, avoid redundant information interfering with production personnel |
| Failure Retry Count | 3 times, 60-second interval | Respond to data pulling failures caused by temporary fluctuations in production systems, ensure workflow stability |
| Version Compatibility | FastGPT v4.17.0 | Adapt to the latest workflow orchestration node configuration and permission management functions, avoid compatibility issues with older versions |
Three common mistakes
- Phenomenon: Workflow output includes generated content from preceding AI nodes, and the configuration to retain only the final aggregated result does not take effect. Cause: The output aggregation rule is not configured in the workflow, and the output display switch for preceding nodes is not disabled.
- Phenomenon: The workflow import function cannot be found in the new version, and the import path from older versions is no longer accessible. Cause: The new version moves the workflow import entry to the resource management module of the team space, and the operation logic of older versions is not adapted.
- Phenomenon: When calling a workflow via API, user selection and form input components do not display interactive prompts. Cause: The interactive node switch for API access is not enabled in the workflow configuration, or the parameters required for interaction are not included in the API request.
How to confirm correct configuration
- Trigger a preset production event, such as simulating a sheet break or uploading a single-roll production record. Check the workflow running log to confirm that the trigger node starts normally and pulls corresponding data.
- Import test paper machine operation records and pulp preparation sheet data. Verify that the format alignment node correctly converts field units and names, with no format errors.
- Run the complete workflow. Review the final output content to confirm that only aggregated process documents or exception reports are retained, with no redundant output from preceding AI nodes.
- Call the configured workflow via API. Verify that user selection and form input components pop up interactive prompts normally, matching expected interaction logic.
The values provided here are common starting points, and should be evaluated against the reader's own samples.