This page is written based on FastGPT v4.17.0.
What Data Looks Like for This Category
Pulp and paper production ledger data comes from wood pulp and waste paper batch records, DCS/QCS systems, on-paper machine measuring equipment, laboratory testing systems, energy and water treatment systems. Data update frequencies fall into three categories: real-time, per shift, and per roll, corresponding to paper machine operating parameters, shift production records, and single-roll finished product ledgers. Daily documents include pulp preparation sheets, beating records, paper machine operation logs, online quality curves, laboratory test reports, and sheet break and product change records. Fields include pulp consistency, beating degree, paper machine speed, grammage, moisture content, and more. Some unstructured documents such as online quality curves are in sequential image format.
What Constraints These Characteristics Impose on Workflow Orchestration
Multi-source production data with varied update frequencies requires workflows to configure differentiated trigger rules per data type, to avoid repeated pulling or missing key ledgers. Diverse document formats require workflows to include built-in structured parsing and unstructured image processing branches, to adapt to tabular files such as pulp preparation sheets and image files such as online quality curves. High data volume from high-speed continuous web production requires workflows to set data processing limits per node, to prevent node overload and timeouts. Unlike finished paper processing scenarios in the printing and packaging category, sheet break and product change records in pulp and paper production are abnormal data, which require separate abnormal branches to handle, to avoid interfering with normal ledger summary processes.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Global Variables | Bind DCS/QCS interface addresses, single-roll production data upper limit | Match the core sources of production data in this category and the boundary threshold for single-roll production |
| Node Trigger Timing | Trigger real-time data every 60 seconds, trigger shift data within 10 minutes after the shift ends, trigger single-roll data when the roll is completed | Adapt to the three update frequencies of real-time, per shift, and per roll for data in this category |
| Supported File Upload Formats | Include CSV, JSON, PNG | Cover document types in this category such as pulp preparation sheets, laboratory reports, online quality curves |
variables | Preset the maximum processing volume for single-roll sequential data as 10000 entries | Match the real-time data output scale of high-speed paper machines, avoid node overload |
| Error Capture Node | Associate nodeId as the unique identifier of the model call node | Accurately capture error information for specified nodes, facilitate problem location |
| Global Variable Acquisition | Extract parameters from the data source mapping configured in the system | Uniformly manage interface parameters of production systems, avoid hardcoding errors |
Three Common Mistakes
- After the workflow starts, image upload testing fails, with the file upload node prompting unsupported file types. The cause is that the PNG file whitelist is not configured, and the image document format of online quality curves is not matched.
- The model call node returns a 429 status code, with an error indicating too many requests. The cause is that the request interval threshold for the node is not configured, and the call quota requirements of Qwen3.5-plus are not adapted to.
- The global variable field in the node is empty, with the inability to obtain interface parameters from the DCS system. The cause is that the data source mapping is not configured in the
variablessettings, and global parameters are not correctly associated.
How to Verify Proper Configuration
- Upload a pulp preparation sheet CSV file, check whether the node correctly parses the category-specific field content.
- Trigger a real-time data pulling task, check whether paper machine operating data from the DCS system is obtained at the preset interval.
- Simulate a model call request that exceeds the quota, check whether the error capture branch is triggered and the corresponding status code is returned.
- View the
variablesconfiguration item, confirm that the bound global variable parameters match the actual configuration of the production system.
The values provided here are common starting points, and should be evaluated against the reader's own samples.