What this category of data looks like
Pulp and paper inspection and process record data originates from wood pulp and waste paper batch ledgers, DCS/QCS control systems, paper machine online measurement equipment, laboratory testing systems, and energy and water treatment systems. Daily generated documents include pulp preparation sheets, beating records, paper machine operation records, online quality curves, laboratory test reports, and sheet break and product change records.
Data update frequencies are divided into three categories: real-time (online measurement values), shift-by-shift (team production ledgers), and per-roll (full-process parameters for a single paper roll). Data fields include pulp ratio, grammage, moisture content, thickness, paper defect type, and more, with corresponding units such as %, g/㎡, mm, and others.
Constraints on workflow orchestration from these characteristics
Multi-source heterogeneous data sources require workflows to support cross-system variable aggregation and field mapping to avoid data misalignment. Real-time updated online measurement data means trigger nodes must match the data refresh rhythm, and cannot rely on fixed-cycle scheduling. Per-roll level data updates require workflows to associate context by batch, to prevent cross-roll data mixing. Complex quality parameters and abnormal events such as sheet breaks and product changes require workflows to configure branch jump logic to adapt to processing flows for different production scenarios, in compliance with FastGPT v4.17.0 node binding rules.
How to configure the workflow
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
| Global variable binding | Map variables by batch fields | Matches the per-roll data association requirements of pulp and paper business, ensures consistent context for the same batch of data |
| Process trigger method | Real-time data change trigger | Adapts to the real-time update frequency of online measurement data, avoids delayed processing |
| Inter-node parameter transfer | Bind upstream and downstream fields by nodeId | Ensures accurate parameter transfer between workflow nodes, avoids data loss |
| Abnormal branch configuration | Trigger branches on sheet break/ product change events | Covers the most time-consuming exception handling links in the business, adapts to production fluctuations |
| API call timeout setting | 600 seconds | Matches the conventional generation cycle of laboratory reports, avoids unnecessary interruptions |
| Retrieval result count limit | Top 10 entries | Narrows the retrieval scope, improves matching efficiency |
| Prompt word length configuration | 800-1200 characters | Adapts to the description length of pulp and paper business parameters, improves AI understanding accuracy |
Three common configuration errors
- Scenario: The workflow executes without further response after reaching the knowledge base search node, with a parameter error status code. Cause: The associated fields for the current batch are not configured in
variables, leading to no scope limitation during retrieval and returning invalid results. - Scenario: Third-party API calls fail when the process starts, with empty field returns. Cause: The API call permission corresponding to
nodeIdis not bound in the process start node, causing the request to fail verification. - Scenario: Historical production records cannot be passed as variables to code nodes, and no corresponding option appears in the global variable list. Cause: The storage mapping of historical records is not configured in
variables, only relying on the default global variable pool without binding business-specific context data.
How to verify a correct configuration
- Open the
variablesconfiguration panel, confirm that all pulp and paper business fields have been bound to corresponding data sources, with no empty mapping items. - Simulate a sheet break event to trigger the workflow, check whether the branch node correctly jumps to the exception handling process.
- Call the test API, confirm that the process start node can correctly obtain the return value and write it to the
variablesvariable pool. - Run a test case for single-roll production data, verify that all workflow nodes execute in sequence without mid-process interruptions.
The values given are common starting points and should be measured against the reader's own samples.